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Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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25 pages, 786 KB  
Review
Review of Literature on Intercomparison Studies Between GPM DPR and Ground-Based Radars
by Zainab S. Ali and Corene J. Matyas
Atmosphere 2026, 17(3), 261; https://doi.org/10.3390/atmos17030261 - 28 Feb 2026
Viewed by 609
Abstract
Intercomparison studies between satellite-based and ground-based radar systems are essential for advancing radar technologies and improving precipitation retrieval algorithms. This study conducted a systematic literature review of Global Precipitation Measurement Mission (GPM) Dual-Frequency Precipitation Radar (DPR) and ground-based radar intercomparison studies using the [...] Read more.
Intercomparison studies between satellite-based and ground-based radar systems are essential for advancing radar technologies and improving precipitation retrieval algorithms. This study conducted a systematic literature review of Global Precipitation Measurement Mission (GPM) Dual-Frequency Precipitation Radar (DPR) and ground-based radar intercomparison studies using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) method, focusing on peer-reviewed literature published between 2014 and 2024. The review synthesizes current knowledge of DPR precipitation detection and estimation, including the application of DPR in ground-based radar calibration, and discussions on retrieval methods and attenuation correction algorithms. Most studies used a volume-matching method to compare observations between datasets and examine S- and C-band radars from national networks. Most analyses occurred over the Northern Hemisphere, and individual ground-based radars were more frequently compared to DPR rather than examining mosaics. Beyond summarizing existing studies, this review identifies systematic, geographic, methodological, and algorithmic gaps that constrain comprehensive validation of DPR products. Recurrent bias patterns—such as precipitation-type-dependent errors and attenuation-related uncertainties—highlight priority areas for algorithm refinement and targeted validation campaigns. By synthesizing validation strategies and recurring performance limitations, this work provides a structured reference for future intercomparison studies, supports more standardized validation practices, and informs the development of improved precipitation retrieval algorithms, ground-based radar calibration practices, and next-generation satellite radar missions. Full article
(This article belongs to the Special Issue Radar Sensing Atmosphere: Modelling, Imaging and Prediction (2nd Edition))
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21 pages, 1254 KB  
Article
Solar and Anthropogenic Climate Drivers: An Updated Regression Model and Refined Forecast
by Frank Stefani
Atmosphere 2026, 17(3), 252; https://doi.org/10.3390/atmos17030252 - 28 Feb 2026
Viewed by 1554
Abstract
Recently, an attempt was made to quantify the respective solar and anthropogenic influences on the terrestrial climate, and to cautiously predict the global mean temperature over the next 130 years. In a double regression analysis, both the binary logarithm of carbon dioxide concentration [...] Read more.
Recently, an attempt was made to quantify the respective solar and anthropogenic influences on the terrestrial climate, and to cautiously predict the global mean temperature over the next 130 years. In a double regression analysis, both the binary logarithm of carbon dioxide concentration and the geomagnetic aa index were used as predictors of the sea surface temperature (SST) since the mid-19th century. The regression results turned out to be sensitive to end effects, leading to a disconcertingly broad range of the climate sensitivity between 0.6 K and 1.6 K per doubling of CO2 when varying the final year of the data used. The aim of this paper is to significantly narrow down this range. To this end, the correlations between the two predictors and the dependent variable (SST) are analysed in detail. It is demonstrated that the SST can be predicted until around 2000 almost perfectly using only the aa index, whereas for later periods the role of CO2 increases significantly. Therefore, the weight of the aa index is fixed to its very robust outcome (around 0.04 K/nT) from the single and double regressions up to 1990. The SST data, reduced by the aa contribution thus specified, are then used in a single regression with CO2 as the only remaining predictor. This results in a significant reduction in the range of CO2 sensitivity, narrowing it to 1.1–1.4 K. Given the exceptionally high temperatures in recent years, these values are considered a kind of upper limit that could still be subject to downward corrections when future data are incorporated. Based on this estimate, a prediction of the temperature up to the year 2100 is ventured, assuming various constant emission scenarios combined with a linear sink model for atmospheric CO2 content. The most risky factor in this prediction is the future of the aa index. For its forecast, the results of a recently developed synchronization model of the solar dynamo are tentatively employed. Full article
(This article belongs to the Special Issue The Challenge of Weather and Climate Prediction (2nd Edition))
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17 pages, 2012 KB  
Article
Impacts of Aerosol Concentration Changes on Cloud Microphysics and Convective Intensity of the Southwest Vortex: Insights from MODIS Observations and Numerical Simulations
by Yan Wang, Tingting Wu and Yimin Wang
Atmosphere 2026, 17(3), 259; https://doi.org/10.3390/atmos17030259 - 28 Feb 2026
Viewed by 417
Abstract
Aerosol–cloud interactions (ACIs) remain a long-standing uncertainty in quantifying cloud microphysical properties, convection, and precipitation. There are fewer investigations into the effects of ACIs on the southwest vortex (a mesoscale circulation with a spatial scale of 300–500 km). Satellite-retrieved MODIS data (2002–2022) reveals [...] Read more.
Aerosol–cloud interactions (ACIs) remain a long-standing uncertainty in quantifying cloud microphysical properties, convection, and precipitation. There are fewer investigations into the effects of ACIs on the southwest vortex (a mesoscale circulation with a spatial scale of 300–500 km). Satellite-retrieved MODIS data (2002–2022) reveals a decreasing trend in the June–August (JJA) seasonal mean ice droplet effective radius (DER_Ice) over the Sichuan Basin (SCB) since 2013, corresponding to China’s emission reduction efforts. Concurrently, post-2013 trends exhibit a positive shift in cloud-top height (CTH) and a negative trend in cloud-top pressure (CTP), collectively indicative of intensified convective activity. This contradicts the conventional conclusion that increased anthropogenic emissions reduce droplet effective radius (DER) and intensify convection under constant cloud water content. To address this discrepancy, we simulated the precipitation event caused by the southwest vortex (SWV) during 11–14 August 2020, under distinct initial aerosol loading (clean vs. polluted), using the fully coupled WRF-ACI-Full cloud-resolving model (incorporating sophisticated aerosol parameterizations). Results show that increased aerosols reduce basin-averaged precipitation by 0.54% and updraft speed by 0.37% in the polluted case compared to the clean case, which is negligible. These findings differ from previous studies on ACI-related cloud and precipitation responses. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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22 pages, 13052 KB  
Article
Enhanced Migratory Biological Echo Extrapolation from Weather Radar Using ISA-LSTM
by Dou Meng, Yunping Liu, Dongli Wu, Zhiliang Deng, Yifu Chen and Chunzhi Wang
Atmosphere 2026, 17(3), 257; https://doi.org/10.3390/atmos17030257 - 28 Feb 2026
Viewed by 351
Abstract
Weather radar provides continuous, large-scale observations of aerial biological activity. However, biological echoes typically exhibit weak signals, sparse distributions, and non-stationary abrupt variations, causing existing extrapolation models to suffer from over-smoothing and loss of detail and making it difficult to capture their short-term [...] Read more.
Weather radar provides continuous, large-scale observations of aerial biological activity. However, biological echoes typically exhibit weak signals, sparse distributions, and non-stationary abrupt variations, causing existing extrapolation models to suffer from over-smoothing and loss of detail and making it difficult to capture their short-term evolution effectively. To address this issue, we propose an Integrated Self-Attention Long Short-Term Memory (ISA-LSTM) model that integrates a self-attention mechanism within the Predictive Recurrent Neural Network (PredRNN) framework. Coupled convolutional modules are introduced to enhance feature interactions between inputs and hidden states, while a spatiotemporal self-attention mechanism improves long-term dependency modeling and local detail preservation. Experiments conducted on 6000 biological echo samples from three weather radars in the Poyang Lake region demonstrate that the proposed model achieves superior extrapolation accuracy and stability compared with existing methods, maintaining a low false-alarm rate for lead times of up to 50 min. The results suggest that ISA-LSTM offers an effective deep learning approach for biological echo extrapolation, with applications in aviation safety and agricultural pest and disease early warning. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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25 pages, 4746 KB  
Article
Variation Characteristics of Evapotranspiration and Water Consumption Effectiveness Evaluation in the Aksu River Basin Based on Multi-Source Data Fusion
by Meie Yang, Guanghui Wei, Shichen Yang and Xiaochen Yao
Atmosphere 2026, 17(3), 244; https://doi.org/10.3390/atmos17030244 - 27 Feb 2026
Viewed by 385
Abstract
In order to improve the robustness and internal consistency of evapotranspiration estimation in arid regions and to reveal the characteristics of water consumption structure within a river basin, this study focused on the Aksu River Basin. Multiple data sources, including the Penman–Monteith model, [...] Read more.
In order to improve the robustness and internal consistency of evapotranspiration estimation in arid regions and to reveal the characteristics of water consumption structure within a river basin, this study focused on the Aksu River Basin. Multiple data sources, including the Penman–Monteith model, MODIS remote sensing products, GRACE terrestrial water storage change data, and the GLDAS–Noah model, were integrated to establish a Bayesian Model Averaging (BMA)-based framework for fusing actual evapotranspiration (ETa) estimates. The results indicate that the BMA integration effectively mitigated model-dependent biases and improved the consistency and robustness of basin-scale ETa estimates. During the period 2000–2020, ETa in the basin exhibited an overall increasing trend (approximately 4.04 mm/a), with a spatial distribution pattern characterized by higher values in the northwest and lower values in the southeast. In terms of water consumption effectiveness, low-effectiveness water consumption predominated in the basin (accounting for 61.24%), while high-effectiveness water consumption accounted for a relatively smaller proportion (26.01%). These results suggest that the current water consumption structure remains dominated by low-effectiveness components, indicating potential room for optimization in balancing irrigation activities and ecosystem water use. The multi-source data fusion and water consumption effectiveness evaluation framework proposed in this study provides a scientific basis for water resource management and ecological water security assessment in arid river basins. Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
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20 pages, 4504 KB  
Article
SSS Retrieval Using C- and X-Band Microwave Radiometer Observations in Coastal Oceans
by Xinyu Li, Xinhao Zuo and Jin Wang
Atmosphere 2026, 17(3), 250; https://doi.org/10.3390/atmos17030250 - 27 Feb 2026
Viewed by 412
Abstract
This study proposes a method for retrieving ocean sea surface salinity (SSS) using C/X-band ocean emissivities in coastal regions, aiming to verify the performance of these unconventional frequencies for SSS retrieval in warm, high-salinity-variation coastal oceans. Since C/X-band brightness temperatures are less sensitive [...] Read more.
This study proposes a method for retrieving ocean sea surface salinity (SSS) using C/X-band ocean emissivities in coastal regions, aiming to verify the performance of these unconventional frequencies for SSS retrieval in warm, high-salinity-variation coastal oceans. Since C/X-band brightness temperatures are less sensitive to sea surface salinity than L-band brightness temperatures, it becomes particularly important to develop a sophisticated and effective method for extracting salinity-related signals from C/X-band brightness temperatures. To this end, a wind effect correction process is developed to remove rough sea surface emissivity contributions from total emissivity and derive calm sea emissivity from WindSat’s brightness temperatures. The wind-induced effects are modeled with a third-order polynomial. Then, based on emissivity analysis, a weighted combination of C/X-band calm sea emissivities (with parameter λ) is introduced to reduce SST sensitivity. This λ-based combination is used to retrieve SSS in the Bay of Bengal. Based on the triple-match method and buoy data, the salinity retrieval results are verified and compared with the Soil Moisture Active Passive (SMAP) SSS and Argo in situ SSS. The results show that the use of parameter λ reduces the RMS error of SSS by 0.1–0.2 psu. The RMSE of SSS retrieval is about 0.64 psu, which is comparable to the error of SMAP data. Simultaneously, the SSS retrieval accuracy is significantly influenced by offshore distance. At an offshore distance of 100 km, the salinity retrieval error exceeds 1 psu, while when the offshore distance exceeds 500 km, the salinity retrieval error is better than 0.6 psu. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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21 pages, 10929 KB  
Article
Spatiotemporal Evolution and Influencing Factors of Air Pollutants in the Three Major Urban Agglomerations of the Yellow River Basin
by Yanli Yin, Fan Zhang, Qifan Wu, Linan Sun, Yuanzheng Li, Peng Wang, Zilin Liu, Tian Cui, Zhaomeng Zhou, Runjing Hou, Mingyang Zhang, Jinping Liu and Qingfeng Hu
Atmosphere 2026, 17(3), 242; https://doi.org/10.3390/atmos17030242 - 26 Feb 2026
Viewed by 523
Abstract
Against the backdrop of the ongoing advancement of China’s dual-carbon goals and the coordinated strategy for ecological protection and high-quality development in the Yellow River Basin (YRB), it is important to clarify the spatiotemporal dynamics of air pollution in the densely populated urban [...] Read more.
Against the backdrop of the ongoing advancement of China’s dual-carbon goals and the coordinated strategy for ecological protection and high-quality development in the Yellow River Basin (YRB), it is important to clarify the spatiotemporal dynamics of air pollution in the densely populated urban agglomerations of the mid–lower YRB. Using station-based daily observations from 2015 to 2024, this study examines six major air pollutants (PM2.5, PM10, CO, NO2, O3 and SO2) across the Shandong Peninsula, Central Plains, and Guanzhong Plain urban agglomerations. Sen’s slope estimator and the Mann–Kendall test are applied to quantify long-term trends, while partial correlation analysis and the GeoDetector model are used to diagnose pollutant co-variations and the drivers of spatial heterogeneity. Results indicate that while PM2.5, PM10, NO2, SO2, and CO concentrations significantly decreased, O3 exhibited a statistically significant upward trend (Z = 2.32, p = 0.02), particularly with pronounced summer maxima. PM2.5 shows clear seasonal variation, with elevated levels during winter and reduced levels during summer. Marked spatial contrasts are also observed: elevated particulate matter and CO are concentrated in the northern part of the Central Plains, while higher O3 levels are more evident in coastal areas, particularly within the Shandong Peninsula urban agglomeration. In terms of inter-pollutant relationships, particulate matter and CO are positively associated with SO2, whereas O3 is negatively correlated with NO2. GeoDetector results further suggest that air temperature, wind speed, and topography are the key factors associated with the spatial differentiation of pollutant levels; notably, the interaction between wind speed and temperature provides the greatest explanatory power, with effects that vary seasonally. These findings provide a scientific basis for region-specific air-pollution control and for advancing the co-benefits of carbon reduction and pollution mitigation in the YRB. Full article
(This article belongs to the Special Issue Atmospheric Pollution Dynamics in China)
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15 pages, 2764 KB  
Article
How Variations in Photosynthetically Active Radiation Affect Vegetation Carbon–Water Coupling Processes: A Study Based on the Vegetation Microclimate Process (VMcP) Model
by Yu Wang, Shufan Li, Xiufeng Sun, Yan Xu and Junru Yan
Atmosphere 2026, 17(3), 238; https://doi.org/10.3390/atmos17030238 - 25 Feb 2026
Viewed by 370
Abstract
Vegetation physiological processes are critical regulators of terrestrial carbon–water cycles and local microclimate dynamics, with photosynthetically active radiation (PAR, 400–700 nm) serving as a primary driving force. However, most vegetation–climate process models simplify the fraction of PAR in global solar radiation as a [...] Read more.
Vegetation physiological processes are critical regulators of terrestrial carbon–water cycles and local microclimate dynamics, with photosynthetically active radiation (PAR, 400–700 nm) serving as a primary driving force. However, most vegetation–climate process models simplify the fraction of PAR in global solar radiation as a constant 50%, potentially introducing diurnal simulation biases that propagate into cumulative annual errors in vegetation carbon–water coupling estimates. To address this limitation, we first evaluated the performance of three empirical models for simulating the dynamic PAR fraction and integrated the most accurate model into the Vegetation Microclimate Process (VMcP) model, and further used typical meteorological year (TMY) data of Beijing, Shanghai and Shenzhen as input to compare the differences in vegetation carbon–water processes before and after the improvement. The results show that the diurnal variation range of PAR fraction in global solar radiation is between 39% and 58%. The existing models that neglect the dynamic changes in PAR may overestimate vegetation transpiration cooling and photosynthetic carbon sequestration by 2.3% and 3.5%, respectively. Meanwhile, Shenzhen (64.3 W/m2; 1.59 g/m2·d), characterized by favorable light and thermal conditions, is more prone to large errors compared with Shanghai (47.6 W/m2; 1.21 g/m2·d) and Beijing (39.5 W/m2; 0.93 g/m2·d). This study provides a novel tool for the accurate assessment of vegetation-mediated microclimate improvement, and offers a new perspective for nature-based climate solutions. Full article
(This article belongs to the Special Issue Agriculture, Ecosystems and Environment: Monitoring, Modeling and Mitigation Under Climate Change)
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23 pages, 8789 KB  
Article
Influence of Urban Morphology on Traffic-Related Air Pollution Dispersion in Urban Environments
by Chiara Metrangolo, Adelaide Dinoi, Gianluca Pappaccogli, Fabio Bozzeda, Antonio Esposito, Prashant Kumar and Riccardo Buccolieri
Atmosphere 2026, 17(3), 234; https://doi.org/10.3390/atmos17030234 - 25 Feb 2026
Viewed by 1333
Abstract
Urban air pollution from road traffic remains a major public health concern, with its spatial variability at neighbourhood scales strongly influenced by urban morphology. This study investigates how urban form affects the dispersion of traffic-related PM2.5 in four Italian cities (Lecce, Bari, [...] Read more.
Urban air pollution from road traffic remains a major public health concern, with its spatial variability at neighbourhood scales strongly influenced by urban morphology. This study investigates how urban form affects the dispersion of traffic-related PM2.5 in four Italian cities (Lecce, Bari, Milan and Rome) representing diverse climatic and morphological contexts. Seasonal simulations were conducted using the ADMS-Roads dispersion model, integrating detailed road geometries, standardized traffic emissions, and city-level meteorological data for 2019–2021. Urban morphology was characterized at 100 m resolution using building plan area fraction (λp), street-canyon aspect ratio and mean building height derived from GIS analyses. Statistical analysis combined random forest regression with partial dependence plots and quantile regression to explore both average and distributional effects. Results reveal a generally negative association between λp and PM2.5 in Lecce, Milan, and Rome, particularly at higher concentration quantiles, suggesting that denser urban fabrics may mitigate extreme pollution episodes. Bari exhibits a weaker and more heterogeneous response, highlighting the influence of local wind regimes and traffic distribution. Wind speed and temperature consistently reduce PM2.5 across all cities, while street geometry effects are non-linear and season-dependent. These findings demonstrate the importance of considering urban morphology alongside traffic and meteorology when designing strategies to reduce exposure. Importantly, the methodological framework presented here, combining high-resolution dispersion modelling with interpretable machine-learning analyses, is transferable to other urban contexts, providing a robust approach to assess morphology–pollution interactions beyond the studied cities. Full article
(This article belongs to the Section Air Quality)
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28 pages, 11156 KB  
Article
Environmental Monitoring and Risk Assessment in Missile Stage Impact Zones Using Mapping Data and a Digital Passport Approach
by Aliya Kalizhanova, Anar Utegenova, Yerlan Bekeshev, Murat Kunelbayev and Zhazira Zhumabekova
Atmosphere 2026, 17(3), 229; https://doi.org/10.3390/atmos17030229 - 24 Feb 2026
Viewed by 724
Abstract
This paper proposes an approach to digitizing the environmental passport for areas where detachable parts of launch vehicles fall in Kazakhstan based on an interactive geographic information system platform and smart maps. An example is considered for zone U-4 (“Ulytau” district of the [...] Read more.
This paper proposes an approach to digitizing the environmental passport for areas where detachable parts of launch vehicles fall in Kazakhstan based on an interactive geographic information system platform and smart maps. An example is considered for zone U-4 (“Ulytau” district of the “Karaganda” region), which includes the fall zones of “Soyuz” launch vehicle blocks (IZ 26, 32, 34, 42, 56). The natural and climatic factors and hazards of the territory are analyzed: the total area of the zones under consideration exceeds 4.1 million hectares, annual precipitation varies between 218 and 289 mm, strong winds of 5.0–6.8 m/s are characteristic, and a high level of fire hazard can develop within 6–7 days. Data on fires for 2021 are provided. For an integrated assessment, a normalized system criterion, environmental sustainability indicator (0–1), has been introduced, aggregating four groups of criteria (chemical, mechanical, pyrogenic, biota) with a breakdown of contributions and calculation of uncertainty (σ and 95% CI). The system criterion of environmental sustainability map identifies local ‘hot spots’ with levels of around 0.8–1.0, while the uncertainty map shows maximums of up to 0.12–0.14 (with background values of ~0.02–0.08), which increases the validity of management decisions on monitoring and reclamation. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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23 pages, 2435 KB  
Article
Blue Hydrogen Cogeneration as an Energy Vector for a Sustainable Future: A Case for Alberta, Canada
by Malcolm MacLeod, Anne Aditola Titcombe and Eric Croiset
Atmosphere 2026, 17(3), 228; https://doi.org/10.3390/atmos17030228 - 24 Feb 2026
Viewed by 727
Abstract
Hydrogen is a promising clean energy vector capable of decarbonizing future energy systems. This study explores blue hydrogen production via a modified autothermal reforming process, integrated with oxy-fuel combustion and carbon capture technologies. The process achieves approximately 99.8% carbon dioxide capture while co-generating [...] Read more.
Hydrogen is a promising clean energy vector capable of decarbonizing future energy systems. This study explores blue hydrogen production via a modified autothermal reforming process, integrated with oxy-fuel combustion and carbon capture technologies. The process achieves approximately 99.8% carbon dioxide capture while co-generating electricity, improving both environmental and economic performance. A detailed techno-economic analysis for Alberta, Canada, shows that hydrogen can be produced at a competitive cost of $1.70 per kilogram, depending on natural gas supply pressure, with CO2 emissions of just 3.82 kg-CO2/kg-H2, meeting stringent international low-carbon thresholds. Key parameters like natural gas supply pressure, oxygen-to-methane ratio, and turbine pressure ratio were optimized for flexibility, efficiency, and cost-effectiveness. Sensitivity analysis identified financial, policy, and grid decarbonization factors as key drivers of production costs. Compared to other methods, this process stands out for its superior environmental and economic outcomes, particularly in regions with ample natural gas and carbon capture infrastructure. The study underscores the importance of process innovation in advancing sustainable blue hydrogen. Full article
(This article belongs to the Special Issue Integrated Air Pollution Control Technology for Energy Transition (Net-Zero Emissions))
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25 pages, 1977 KB  
Review
Catalytic Conversion of CO2 to Methanol: Advances in Catalyst Design and Plasma-Assisted Technology
by Tao Zhu, Tongyu Shi, Xueli Zhang, Bo Yuan and Chen Li
Atmosphere 2026, 17(2), 224; https://doi.org/10.3390/atmos17020224 - 22 Feb 2026
Viewed by 1407
Abstract
The hydrogenation of CO2 to methanol is a crucial route for achieving carbon recycling. Among the extensively studied catalysts, copper-based catalysts suffer from insufficient activity and stability, while noble metal catalysts are limited by prohibitively high cost. In contrast, metal–organic framework (MOF) [...] Read more.
The hydrogenation of CO2 to methanol is a crucial route for achieving carbon recycling. Among the extensively studied catalysts, copper-based catalysts suffer from insufficient activity and stability, while noble metal catalysts are limited by prohibitively high cost. In contrast, metal–organic framework (MOF) materials demonstrate unique advantages due to their designable architectures and high dispersion. Conventional thermal catalysis relies on high temperature and pressure; photocatalysis suffers from low efficiency; and electrocatalysis shows poor selectivity. These limitations motivate the exploration of new catalytic approaches. Plasma catalysis, particularly dielectric barrier discharge (DBD) technology, can efficiently activate CO2 via high-energy electrons and reactive species at ambient temperature and pressure, and generate a synergistic effect with catalysts, significantly enhancing methanol production efficiency and selectivity. Studies have shown that plasma–catalyst synergistic systems, such as those employing Cu/γ-Al2O3 or Pt/In2O3, exhibit superior performance to individual processes under mild conditions. Future research should focus on elucidating the plasma–catalyst interface mechanism, optimizing reactor design, and developing compatible, high-efficiency catalysts to establish a novel pathway for CO2 conversion with low energy consumption and high efficiency. Full article
(This article belongs to the Special Issue Air Pollution Control in China: Progress, Challenges, and Perspectives (3rd Edition))
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28 pages, 1824 KB  
Article
Multivariate Analysis of Factors Influencing the Concentration of Persistent Organic Pollutants and Microplastics in Mosses Sampled Across Germany in 2020
by Stefan Nickel, Winfried Schröder, Annekatrin Dreyer, Christine Kube and Carmen Wolf
Atmosphere 2026, 17(2), 223; https://doi.org/10.3390/atmos17020223 - 21 Feb 2026
Cited by 1 | Viewed by 535
Abstract
Mosses (Bryophyta) are well-established biomonitors of atmospheric deposition, including persistent organic pollutants (POPs) and microplastics (MPs). Using German Moss Survey 2020 data, this study identified factors influencing POPs and MPs in mosses through correlation and random forest analyses. For 10 of 11 POP [...] Read more.
Mosses (Bryophyta) are well-established biomonitors of atmospheric deposition, including persistent organic pollutants (POPs) and microplastics (MPs). Using German Moss Survey 2020 data, this study identified factors influencing POPs and MPs in mosses through correlation and random forest analyses. For 10 of 11 POP groups, the models explained a variance of more than 20%. Key predictors included atmospheric deposition and the density of urban–industrial and agricultural land uses within 100–300 km. Population density and the density of extraction and dump sites within radii of <5 km (PCDD/Fs, PCDD/F TEQ values, HBCD, 23 PBDEs, BDE-209, DBDPE, PBT, and HBBz), as well as distances to residential areas and transport infrastructure (PCDD/Fs, HBCD, PBDEs, DP, and DBDPE), also proved to be highly relevant, although a direct causal relationship seems unlikely for flame retardants. These findings indicate that POP concentrations in mosses are influenced not only by large-scale atmospheric deposition but also by local emission sources near sampling sites. Vegetation parameters, particularly the leaf area index, showed additional effects. For MP, only two polymer groups (SBR and PE) yielded models with sufficient predictive strength, again dominated by proximity to local sources. Minimum sample size analysis demonstrated that a denser sampling network is required to achieve a 20% tolerance error in future monitoring campaigns. Full article
(This article belongs to the Special Issue Biomonitoring Air Pollution for a Healthier Planet)
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10 pages, 511 KB  
Article
Development of Odour Intensity Reference Solutions for Environmental Odour Evaluation
by Takaya Higuchi and Yingchao Cheng
Atmosphere 2026, 17(2), 222; https://doi.org/10.3390/atmos17020222 - 21 Feb 2026
Viewed by 451
Abstract
For the appropriate evaluation of environmental odours, it is necessary to develop a reliable odour measurement scale. Odour intensity is one of the main odour characterisation parameters and a remarkably common and important sensory indicator of environmental odours. In this study, the odour [...] Read more.
For the appropriate evaluation of environmental odours, it is necessary to develop a reliable odour measurement scale. Odour intensity is one of the main odour characterisation parameters and a remarkably common and important sensory indicator of environmental odours. In this study, the odour intensity level between two and four of the six-point odour intensity scale was focused on, and odour intensity reference solutions of representative odorants for environmental odour evaluation were developed. As a result, propionic acid, propylamine, ethyl acetate, and isobutyraldehyde were selected as representative odorants, and three concentration steps of each odorant were determined to cover the odour intensity of two, three, and four of the six-point odour intensity scale. These reference odour solutions will be applicable to the training of inexperienced panel members and reliable on-site investigations of environmental odours. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (4th Edition))
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22 pages, 2267 KB  
Article
Spatio-Temporal Variation Characteristics of PM2.5 and O3 in the Yellow River Great Bend Urban Agglomeration from 2020 to 2023
by Shangpeng Sun, Xiaoli Xia and Zhenyu Tian
Atmosphere 2026, 17(2), 220; https://doi.org/10.3390/atmos17020220 - 20 Feb 2026
Cited by 1 | Viewed by 472
Abstract
The Yellow River Great Bend Urban Agglomeration is a key area in the ecological protection and high-quality development strategy of the Yellow River Basin. In the process of coordinated regional development, the contradiction between economic development and environmental protection has become increasingly prominent, [...] Read more.
The Yellow River Great Bend Urban Agglomeration is a key area in the ecological protection and high-quality development strategy of the Yellow River Basin. In the process of coordinated regional development, the contradiction between economic development and environmental protection has become increasingly prominent, and the pollution problems of PM2.5 and O3 have become prominent. Based on the observation data of air pollutants and meteorological data of 15 cities from 2020 to 2023, this study explored the spatio-temporal variation characteristics of PM2.5 and O3 concentrations in this region and the influence of meteorological factors (temperature, relative humidity, wind speed, and precipitation). The results showed that the proportion of days with good air quality in the Yellow River Great Bend Urban Agglomeration metropolitan area increased first and then decreased from 2020 to 2023. PM2.5 concentrations were highest in winter and lowest in summer, with moderate levels in spring and autumn. In contrast, O3 concentrations peaked in summer and reached their lowest levels in winter. In terms of spatial variation, the spatial distribution of the number of PM2.5 polluted days roughly decreases from northwest to southeast, with Taiyuan City having the largest number of polluted days. The number of days with O3 pollution roughly shows a pattern of more in the middle and less around the periphery. Spatial autocorrelation analysis indicates that the PM2.5 concentration and O3 concentration in the Yellow River Great Bend Urban Agglomeration have obvious high-value and low-value spatial agglomeration characteristics. Meteorological elements have a significant influence on the concentrations of PM2.5 and O3. The occurrence frequencies of PM2.5 pollution and O3 pollution were significantly higher respectively within the temperature ranges of −10 to 15 °C and 20 to 30 °C, as well as under the condition of RH > 50% and in the range of 30% to 70% of the relative humidity. Statistical analysis revealed a universally significant negative correlation between wind speed and PM2.5 concentrations across all cities (mean R = −0.09, binomial test p < 0.001), confirming the critical role of stagnant conditions in local pollutant accumulation. The results of this study can provide important references for regional precise pollution control and environmental quality improvement and are of great significance for promoting regional sustainable development. Full article
(This article belongs to the Section Air Quality)
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22 pages, 7126 KB  
Article
A Climatology of Low-Level Jets at the Tiksi Observatory (Laptev Sea, Siberia) Using High-Resolution Regional Climate Model Simulations
by Günther Heinemann and Lukas Schefczyk
Atmosphere 2026, 17(2), 218; https://doi.org/10.3390/atmos17020218 - 20 Feb 2026
Viewed by 529
Abstract
Low-level jets (LLJs) are important mesoscale features in the Arctic and are highly relevant for the atmospheric transport of heat, moisture, and air pollutants, as well as for wind energy and aircraft operations. In this paper, LLJs at the Tiksi observatory in the [...] Read more.
Low-level jets (LLJs) are important mesoscale features in the Arctic and are highly relevant for the atmospheric transport of heat, moisture, and air pollutants, as well as for wind energy and aircraft operations. In this paper, LLJs at the Tiksi observatory in the Laptev Sea region are investigated during the period 2014–2020 using simulations performed with the regional climate model CCLM with a 5 km resolution. The main synoptic weather patterns for LLJs at Tiksi were identified using a self-organizing map (SOM) analysis. LLJs occurred in about 55% of all profiles with an average height of about 400 m and an average speed of about 13 m/s. About 60% of the LLJs had core speeds larger than 10 m/s (strong jets). The occurrence frequency for all jets showed a pronounced seasonal cycle with more and stronger LLJs during winter. The turbulent kinetic energy in the lower ABL was four times as large for LLJs than for situations without LLJs, which underlines the impact of LLJs on turbulent processes in the ABL. The mean duration of LLJ events (duration of at least 6 h) was almost 24 h and the 90th percentile was about two days. About 70% of the LLJ events were associated with downslope winds of the local mountain ridge and had a longer duration of about three days for the 90th percentile. Full article
(This article belongs to the Section Meteorology)
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28 pages, 12075 KB  
Article
Research on the Driving Mechanism of Water and Sediment Evolution in the Area of the Datengxia Water Control Hub Project: Principle Analysis, Method Design, and Prediction Simulation
by Chengyong Gong, Yinying Wang, Weitao Weng, Shiming Chen and Xinyu Guo
Atmosphere 2026, 17(2), 217; https://doi.org/10.3390/atmos17020217 - 19 Feb 2026
Viewed by 533
Abstract
This study investigates the characteristics of water and sediment evolution under the influence of the Datengxia Water Control Hub Project by analyzing its affected area, with a focus on the driving mechanisms of human activities on these processes. Utilizing hydrological data (1993–2022) from [...] Read more.
This study investigates the characteristics of water and sediment evolution under the influence of the Datengxia Water Control Hub Project by analyzing its affected area, with a focus on the driving mechanisms of human activities on these processes. Utilizing hydrological data (1993–2022) from the Wuxuan and Dahuangjiangkou Stations, along with meteorological, land use, and population data, we applied the M–K (Mann–Kendall) trend test, Pettitt change point test, double mass curve method, and a random forest model. These methods were used to quantify the contributions of rainfall and human activities and to identify the dominant controlling factors. Model reliability was verified by comparing predicted and observed P-III (Pearson Type III distribution curve), enabling an assessment of water–sediment changes before and after the project’s construction. The results indicate that (1) both stations showed a non-significant declining trend in runoff and sediment load, with a human activity-induced change point detected in 2003; (2) human activities accounted for 93.18% and 92.38% of the reduction in runoff and sediment load at Wuxuan Station, and 74.44% and 54.33% at Dahuangjiangkou Station, respectively; (3) population density was the dominant factor for water–sediment changes at Wuxuan Station (influence weight: 0.41), while grassland area (0.41) and population density (0.40) primarily controlled runoff and sediment changes, respectively, at Dahuangjiangkou Station; (4) following project construction, the trend of the decreasing flood inundation extent with increasing frequency became more pronounced, and sediment deposition was concentrated mainly in the reservoir area and downstream reaches. The study confirms the dominant role of human activities in the basin’s water–sediment dynamics, and the established methodological framework provides a scientific basis for integrated watershed management and ecological conservation. Full article
(This article belongs to the Special Issue Compound Extreme Events in a Changing Climate: Atmospheric Mechanisms and Hydrological Consequences)
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15 pages, 1669 KB  
Article
Impact of Large-Scale Wildfires and Meteorological Factors on PM Concentrations in Agricultural Regions: Non-Linear Relationship Analysis Using GAM
by Hee-Jin Kim, Ki-Youn Kim and Jin-Ho Kim
Atmosphere 2026, 17(2), 216; https://doi.org/10.3390/atmos17020216 - 19 Feb 2026
Viewed by 614
Abstract
The intensification of large-scale wildfires, driven by climate change, presents a critical threat to agricultural ecosystems, specifically during the vulnerable sowing season in March. Departing from the prevailing focus on urban air quality, this study elucidates the spatiotemporal dynamics of particulate matter (PM) [...] Read more.
The intensification of large-scale wildfires, driven by climate change, presents a critical threat to agricultural ecosystems, specifically during the vulnerable sowing season in March. Departing from the prevailing focus on urban air quality, this study elucidates the spatiotemporal dynamics of particulate matter (PM) in eight major Korean agricultural regions during the March 2025 wildfires. By employing a Generalized Additive Model (GAM), we characterized the complex non-linear interactions between PM concentrations and meteorological variables. The analysis reveals a substantial elevation in PM levels during the wildfire event relative to the pre-fire baseline. Most notably, the Sangju region experienced the most acute accumulation, with PM-10 and PM-2.5 concentrations surging by 74% and 46%, respectively; this intensification was significantly compounded by topographic trapping and surface inversion phenomena. Furthermore, GAM results identified temperature and relative humidity as the primary determinants of PM retention, whereas wind speed demonstrated a distinct non-linear, U-shaped effect, facilitating particulate resuspension at higher velocities. These findings quantitatively underscore the susceptibility of agricultural environments to wildfire-induced aerosols and highlight the imperative for establishing agriculture-specific monitoring networks and early warning protocols to safeguard crop productivity. Full article
(This article belongs to the Section Air Quality)
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16 pages, 3114 KB  
Article
The 2025 Extreme Dust Events in China: Evidence, Attribution, and Implications for Regional Air Quality Assessment
by Shengkai Wang, Xiao-Yi Yang and Chenghan Luo
Atmosphere 2026, 17(2), 213; https://doi.org/10.3390/atmos17020213 - 18 Feb 2026
Viewed by 1450
Abstract
Dust activity is controlled by multiple environmental factors and exhibits substantial spatiotemporal and interannual variability. In spring 2025, China experienced unusually frequent dust storms. Surface meteorological observations and PM10 levels show that dust events in 2025 were the most frequent and intense [...] Read more.
Dust activity is controlled by multiple environmental factors and exhibits substantial spatiotemporal and interannual variability. In spring 2025, China experienced unusually frequent dust storms. Surface meteorological observations and PM10 levels show that dust events in 2025 were the most frequent and intense of the last decade. The dust event analysis indicates a pronounced change in transport pathways, with affected regions extending to Central, Southwest, and South China. This differs markedly from the 2021 and 2023 events, which impacted northern China more broadly. Source attribution indicates that the Gobi Desert was the dominant contributor to downstream dust, accounting for 80.0%, 83.1%, and 78.6% of dust concentrations in North, Southwest, and South China, respectively. In addition, enhanced surface winds over the Gobi Desert were identified as the primary drivers of intensified dust emissions, while concurrent changes in precipitation, soil moisture, and vegetation cover played secondary roles. An anomalous low-pressure system over the Bohai–Yellow Sea facilitated northerly wind anomalies, enabling long-range southward dust transport from the Gobi Desert all the way to southern China. These findings improve our understanding of extreme dust events and emphasize the need to consider both emission strength and transport efficiency in regional air quality assessments. Full article
(This article belongs to the Section Meteorology)
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23 pages, 7665 KB  
Article
First Observation of Offshore Gradient of CO2 and CH4 Concentration in Southeast China from 21° N to 32° N Based on Shipborne Campaign
by Yiwei Xu, Jie Wang, Libin Zhu, Na Ma, Jie Qin, Jiandong Xia, Wenjie Hu, Chen Deng, Lewei Zeng, Wilson B. C. Tsui and Xiaoquan Song
Atmosphere 2026, 17(2), 214; https://doi.org/10.3390/atmos17020214 - 18 Feb 2026
Viewed by 683
Abstract
A shipborne campaign was conducted in China’s southeastern coastal waters (21° N–32° N) from 14 to 31 January 2024 to investigate atmospheric CO2 and CH4 concentrations and their offshore gradients. Advanced instrumentation enabled high-precision measurements, validated by canister sampling with strong [...] Read more.
A shipborne campaign was conducted in China’s southeastern coastal waters (21° N–32° N) from 14 to 31 January 2024 to investigate atmospheric CO2 and CH4 concentrations and their offshore gradients. Advanced instrumentation enabled high-precision measurements, validated by canister sampling with strong correlations to reference data. The voyage employed a dual-route design: a northbound baseline along the mainland coast and a southbound route with offshore excursions up to 80 nm, facilitating the first quantification of GHG gradients in the continental shelf region. Baseline concentrations from the northbound route revealed regional variability: CO2 levels ranged from 422.75 ± 9.96 ppm (Fujian) to 445.62 ± 1.51 ppm (Zhejiang), while CH4 levels spanned 2005.78 ± 5.89 ppb (Fujian) to 2064.59 ± 13.93 ppb (Zhejiang). Southbound analysis at 10 nm intervals showed CO2 gradients transitioning from positive to negative at ~30 nm and back to positive at ~70 nm, whereas CH4 exhibited complex behavior, including a positive–negative–positive transition at 30–40 nm and consistent increase beyond 50 nm. Under winter monsoon conditions, transport flux analysis identified eastward CO2 fluxes of 3819.55–6587.77 g·m−2·s−1 and CH4 fluxes of 6.42–11.42 g·m−2·s−1. Southward transport diminished along the coast, with CO2 fluxes declining from 5741.07 to 879.76 g·m−2·s−1 and CH4 fluxes from 9.84 to 1.49 g·m−2·s−1 between Zhoushan and Hong Kong. The Taiwan Strait demonstrated a funneling effect, enhancing southward transport. These findings address data gaps in ocean regions and provide insights for future GHG monitoring. Full article
(This article belongs to the Special Issue Ocean–Atmosphere–Land Interactions and Their Roles in Climate Change (2nd Edition))
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19 pages, 6649 KB  
Article
Field Evaluation of Residential Ventilation Performance Using Simultaneous Multi-Pollutant Generation and Continuous Monitoring
by Taeyon Hwang, Gon Kim, Joowook Kim and Beungyong Park
Atmosphere 2026, 17(2), 212; https://doi.org/10.3390/atmos17020212 - 17 Feb 2026
Cited by 1 | Viewed by 612
Abstract
This study evaluates the feasibility of continuous indoor pollutant monitoring as an indirect method for assessing extended ventilation performance in residential buildings. This research addresses key limitations of conventional short-term tracer-gas methods, which cannot account for occupant lifestyle, environmental fluctuations, and extended ventilation [...] Read more.
This study evaluates the feasibility of continuous indoor pollutant monitoring as an indirect method for assessing extended ventilation performance in residential buildings. This research addresses key limitations of conventional short-term tracer-gas methods, which cannot account for occupant lifestyle, environmental fluctuations, and extended ventilation variability. The study employs a diffusion-based framework to interpret pollutant-concentration equalization across the residential space over extended monitoring periods. We conducted field experiments in an apartment unit equipped with both ducted and non-ducted ventilation systems. Pollutants (PM2.5, CO2, HCHO, and aromatic VOCs (BTEX + styrene)) were uniformly emitted. PM2.5 and CO2 were continuously monitored at six spatially distributed points using calibrated sensors, while HCHO and aromatic VOCs were quantified by repeated active sampling and laboratory analysis. Under ducted ventilation, average pollutant reduction rates reached 86.8% for PM2.5, 58.3% for CO2, and 53.6% for HCHO. Simultaneously, spatial concentration variance decreased by up to 71% within 120 min, indicating strong diffusion-driven equalizations. These results support the feasibility of extended ventilation performance monitoring using continuous pollutant sensing, with implications for IAQ management, energy optimization, and future integration with data-driven predictive models. Full article
(This article belongs to the Section Air Pollution Control)
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16 pages, 7677 KB  
Article
Simulation Analysis of Future Sulfate Aerosol Emissions on the Radiation–Cloud–Climate System
by Chunjiang Zhou, Zhaoyi Lv, Hongwei Yang, Ruiqing Li, Shuangchun Lv and Lin Chen
Atmosphere 2026, 17(2), 208; https://doi.org/10.3390/atmos17020208 - 14 Feb 2026
Viewed by 502
Abstract
This study uses a globally coupled climate framework to examine how regional differences in sulfate emissions, through both direct and indirect aerosol effects, regulate interactions between clouds and radiation and drive nonlinear thermodynamic and hydrological responses in the East Asia and South Asia [...] Read more.
This study uses a globally coupled climate framework to examine how regional differences in sulfate emissions, through both direct and indirect aerosol effects, regulate interactions between clouds and radiation and drive nonlinear thermodynamic and hydrological responses in the East Asia and South Asia summer monsoon region. We employ the Community Earth System Model to compare the Shared Socioeconomic Pathways 1–2.6 and 5–8.5 against the historical scenario with perturbations of anthropogenic sulfate. The results reveal regional contrasts in sulfate concentration and aerosol optical depth: direct shortwave radiation increases in East Asia, while South Asia experiences radiation weakening due to higher aerosol optical depth. Indirect aerosol effects induce cloud adjustments, with East Asia developing more low clouds and higher cloud droplet number concentrations and liquid water paths, leading to greater attenuation of surface shortwave radiation and changes in precipitation and convection. Over the Tibetan Plateau, a higher fraction of high clouds and changes in cloud-top heights jointly drive warming, raising net radiation and strengthening both latent-heat and sensible-heat release. South Asia exhibits a north–south oriented precipitation pattern, with intensified warm advection but a distribution shaped by upper and mid-tropospheric circulations. Overall, the coupling of cloud macro-distribution and cloud microphysics emerges as the principal driver, with direct and indirect effects amplifying nonlinear regional responses. To improve predictability, we advocate multi-model comparisons, observational constraints, tighter bounds on cloud-droplet size distributions, liquid water paths, and cloud droplet number concentrations. Full article
(This article belongs to the Special Issue Atmospheric Pollution Dynamics in China)
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16 pages, 5052 KB  
Article
New Particle Formation and Source Apportionment of Particle Number Size Distribution in the Urban Area of the City of Belgrade
by Željko Ćirović, Danka B. Stojanović, Miloš Davidović, Antonije Onjia, Andres Alastuey and Milena Jovašević-Stojanović
Atmosphere 2026, 17(2), 205; https://doi.org/10.3390/atmos17020205 - 14 Feb 2026
Viewed by 776
Abstract
Ultrafine particles (UFPs) are particles which can penetrate deeply into the respiratory system due to their small size and can translocate into the bloodstream, where they are linked to oxidative stress, inflammation, and adverse cardiovascular outcomes. Ultrafine particles can originate from direct emissions [...] Read more.
Ultrafine particles (UFPs) are particles which can penetrate deeply into the respiratory system due to their small size and can translocate into the bloodstream, where they are linked to oxidative stress, inflammation, and adverse cardiovascular outcomes. Ultrafine particles can originate from direct emissions or processes of new particle formation (NPF) which we investigated in this study. New particle formation is the process by which molecular clusters form and then grow to larger particles and develop to nucleation and Aitken mode particles. This study presents a detailed analysis of ultrafine particle dynamics in the city of Belgrade, Serbia, based on high-resolution particle number size distribution (PNSD) measurements performed at an urban background site in the period from January to March 2020. A total of seven factors were identified using Positive Matrix Factorization (with contributions in brackets): three attributed to traffic, including mixed source (55%), biomass burning (26%), nucleation (11%), and urban diffuse (8%) sources. The results were obtained by measuring size-resolved number concentrations (10–400 nm) and other pollutants (NO, NO2, NOx, CO, O3, PM1, PM2.5, PM10, equivalent black carbon, organic carbon). Wind directional analysis revealed clear spatial signatures, with nucleation linked to south-western winds and primary factors associated with major local emission influences. The results provide the first combined characterization of new particle formation processes and source-resolved ultrafine particle contributions in Belgrade, offering new insights into wintertime urban exposure in Southeastern Europe. Full article
(This article belongs to the Special Issue Chemistry, Environmental Effects, and Source Analysis of Particulate Matter (2nd Edition))
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19 pages, 3179 KB  
Article
Enhanced Thunderstorm Forecasting over the South China Sea Through VLF Lightning Data Assimilation
by Tong Xiao, Zhihong Lu, Qiyuan Yin, Zhe Cai and Hui Li
Atmosphere 2026, 17(2), 197; https://doi.org/10.3390/atmos17020197 - 13 Feb 2026
Viewed by 631
Abstract
To advance marine thunderstorm forecasting and enhance the operational utility of lightning data, this study developed a novel very low-frequency (VLF) lightning data assimilation scheme for the South China Sea region. The three-dimensional graupel mixing ratio field was successfully inverted from VLF lightning [...] Read more.
To advance marine thunderstorm forecasting and enhance the operational utility of lightning data, this study developed a novel very low-frequency (VLF) lightning data assimilation scheme for the South China Sea region. The three-dimensional graupel mixing ratio field was successfully inverted from VLF lightning detection data through the application of an empirical formula linking lightning frequency to graupel mass, a database of graupel mixing ratio profiles, and a distance-weighted diffusion scheme. This reconstructed field was then subjected to horizontal diffusion and assimilated into the Weather Research and Forecasting (WRF) model using the Grid Nudging module within the WRF–Four-Dimensional Data Assimilation (WRF-FDDA) system. A quantitative evaluation of 37 nocturnal marine convective cases was conducted using Fengyun-4A(FY-4A) satellite observations. The results demonstrate that the proposed assimilation method significantly enhances short-term (0–6 h) forecast performance. Specifically, the Fractions Skill Score (FSS) derived from the Advanced Geosynchronous Radiation Imager (AGRI) data increased rapidly during the early forecast stage, exceeding a value of 0.9. Meanwhile, the Lightning Mapping Imager Event (LMIE) product evaluation showed a high probability of detection (POD) of 85% for lightning forecasts, with a false alarm ratio (FAR) of only 9%. These findings indicate that the assimilation approach improves the accuracy of capturing the spatial structure and evolution of convective systems. Although the degree of improvement diminished with longer lead times, the results confirm the value of VLF lightning data in initializing convective-scale processes and underscore its practical value in marine nowcasting applications. Full article
(This article belongs to the Special Issue Atmospheric Electricity (2nd Edition))
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32 pages, 6003 KB  
Article
Characterization of Coarse Organic Particulate Matter in Urban and Rural Switzerland Using Advanced Offline Mass Spectrometry
by Kristty Stephanie Schneider-Beltran, Tianqu Cui, Roberto Casotto, Houssni Lamkaddam, Anna Tobler, Yufang Hao, Peeyush Khare, Manousos Manousakas, Lubna Dada, Stuart K. Grange, Christoph Hueglin, Gaëlle Uzu, Jean-Luc Jaffrezo, Juanita Rausch, David Jaramillo-Vogel, Claudia Mohr, Imad El-Haddad, Jay G. Slowik, André S. H. Prévôt and Kaspar R. Daellenbach
Atmosphere 2026, 17(2), 199; https://doi.org/10.3390/atmos17020199 - 13 Feb 2026
Viewed by 914
Abstract
Although the organic fraction of PM2.5 has been extensively studied, there is a considerable gap in understanding the organic fraction of coarse particles with diameters between 2.5 and 10 µm. We investigate the composition of coarse organic aerosol (OA) across rural, suburban, [...] Read more.
Although the organic fraction of PM2.5 has been extensively studied, there is a considerable gap in understanding the organic fraction of coarse particles with diameters between 2.5 and 10 µm. We investigate the composition of coarse organic aerosol (OA) across rural, suburban, and urban areas of Switzerland. Using Aerosol Mass Spectrometer analyses of water-soluble OA extracted from collected filter samples (one entire year, 441 samples per size fraction), we identified two distinct classes of coarse OA. The first class, which constitutes 41–81% of coarse organic carbon (OC), is associated with primary biological organic carbon (PBOC). PBOC is characterized by specific marker ions (e.g., C2H5O2+) and exhibits pronounced seasonal variation, with peak concentrations observed in the summer. This seasonal trend correlates with that of molecular markers such as arabitol and mannitol, as well as the fraction of biological particles determined by automated scanning electron microscopy coupled to energy dispersive X-ray spectroscopy of individual particles. The second class, contributing 7.9–17.8% to OCcoarse, is denoted as sulfur-containing organic carbon (SCOC) due to the presence of sulfur-containing ions such as CH3SO2+. Elevated concentrations of SCOC in urban environments near roadways suggest a strong influence from non-exhaust traffic emissions and resuspended dust. While the overall variation in coarse OC between rural and urban areas is approximately 10%, PBOC concentrations are 1.4 times higher in rural areas, whereas SCOC concentrations are 1.5 times higher in urban settings. Overall, our study shows that although OCcoarse concentrations in Switzerland are relatively consistent across site types, major water-soluble sources, particle properties and composition vary considerably geographically and seasonally. Full article
(This article belongs to the Section Air Quality)
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23 pages, 2424 KB  
Article
High-Time-Resolution Aerosol Chemistry and Machine-Learning Sensitivity Reveal a Highland Triad Mechanism Driving PM2.5 in Xining (Qinghai–Tibet Plateau)
by Zihong Liang, Xiaofeng Hu, Anan Qi, Guojuan Qu, Weijun Song and Chunyan Sun
Atmosphere 2026, 17(2), 200; https://doi.org/10.3390/atmos17020200 - 13 Feb 2026
Viewed by 825
Abstract
Fine particulate matter (PM2.5) formation mechanisms in fragile highland ecosystems remain inadequately constrained, particularly regarding thermodynamic non-linearities (aerosol pH, liquid water content) and their interaction with geochemical modulation. Here, we present comprehensive year-long online measurements from Xining, Qinghai-Tibet Plateau, integrating hourly [...] Read more.
Fine particulate matter (PM2.5) formation mechanisms in fragile highland ecosystems remain inadequately constrained, particularly regarding thermodynamic non-linearities (aerosol pH, liquid water content) and their interaction with geochemical modulation. Here, we present comprehensive year-long online measurements from Xining, Qinghai-Tibet Plateau, integrating hourly measurements of water-soluble ions, inorganic elements, and gaseous precursors with ISORROPIA-II thermodynamic modeling and ensemble machine learning. Median pH was 4.38 but exhibited two distinct pH regimes (14.8% pH < 3.0, 11.5% pH > 7.2), with acute acidification enhancing toxic metal solubility (Fe, Pb by 3-5×), and it posed distinct ecological risks. Our analysis reveals a distinct “highland mechanism triad” governing PM2.5 dynamics: (1) winter meteorological confinement amplifying dust-catalyzed sulfate formation (SOR = 0.68); (2) spring alkaline dust buffering (pH > 7.2) that titrates NH3 and suppresses nitrate formation (NOR < 0.10); and (3) summer photochemical oxidation constrained by chronic NH3 limitation within an oxidant-excess regime. Random Forest achieved optimal prediction for the chemically active inorganic fraction (RMSE = 6.63 μg/m3, R2 = 0.91) by learning regime-specific non-linearities, with local sensitivity analysis identifying Ca2+, SO42−, and Al as chemically sensitive drivers (S > 0.35) while revealing NH3’s seasonally variable influence (rank 15 in winter, significant in summer; S > 0.28), subsequently complemented by global SHAP analysis, which further revealed NO3− as the most robust predictor (ranking 1st–2nd) and captured NH3’s non-linear threshold effects (). Positive Matrix Factorization apportioned secondary aerosols (30.11%) within a unique alkaline–dust matrix. These findings demonstrate that highland PM2.5 inorganic chemistry operates through fundamentally different pathways than lowland photochemical haze, with acid-induced toxic metal activation providing a new target for ecological protection in this fragile ecosystem. Seasonally adaptive mitigation is required: concurrent SO2-NH3 control in winter, dust suppression infrastructure in spring, and agricultural NH3 capture in summer. This integrated framework provides a transferable methodology for air-quality management in alkaline dust-dominated, NH3-limited highland ecosystems (>2000 m). 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)
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24 pages, 4235 KB  
Article
Uncovering Synergies in Greenhouse Gas and Air Pollutant Reductions in a Comprehensive Industrial City in Northern China
by Zekun Zhang, Yubo Pang, Xiahong Shi, Junting Shi, Huifang Zhang and Jinping Cheng
Atmosphere 2026, 17(2), 204; https://doi.org/10.3390/atmos17020204 - 13 Feb 2026
Viewed by 715
Abstract
Coordinated mitigation of greenhouse gases (GHGs) and air pollutants (APs) offers an effective strategy to address climate and air quality challenges, yet systematic evaluations in medium-sized industrial cities remain limited, despite their coal-dependent energy systems and emission-intensive manufacturing that disproportionately shape national emission [...] Read more.
Coordinated mitigation of greenhouse gases (GHGs) and air pollutants (APs) offers an effective strategy to address climate and air quality challenges, yet systematic evaluations in medium-sized industrial cities remain limited, despite their coal-dependent energy systems and emission-intensive manufacturing that disproportionately shape national emission trajectories. Thus, this study focuses on Weifang, a representative industrial city in Shandong Province, developing a high-resolution, multi-pollutant inventory and applying quantitative synergy indices to characterize emission patterns, sectoral contributions, and hotspot regions. In 2023, Weifang’s total emissions comprised 114.54 million metric tons (Mt) CO2, 121.91 thousand metric tons (kt) CH4, and 27.67 kt N2O, alongside major APs including CO (662.99 kt), TSP (154.44 kt), and NOx (100.83 kt). Industrial sources and electricity-heat production contributed over 80% of CO2 and SO2, while agriculture dominated CH4 (59.5%) and N2O (40.5%). Mobile sources accounted for 66.6% of NOx, over 20% of VOCs, and 61.4% of CO. Spatially, suburban areas produced over 65% of total emissions due to heavy industry and agriculture, whereas the urban core exhibited higher intensities but lower total contributions. Bivariate and integrated synergy indices revealed stronger SO2-NOx-CO2 synergies in the urban core, while suburban emissions were more heterogeneous and spatially dispersed. Synergy analysis indicated strong SO2-CO2 co-variation from shared industrial sources but weak NOx-CO2 correlations due to divergent origins. Hotspot mapping identified industrial parks, power plants, steel zones, and suburban agriculture as priority control areas. These findings demonstrate that source-specific measures are critical to maximizing co-benefits. The proposed methodological framework offers transferable insights for evaluating emission synergies in other industrial cities. Full article
(This article belongs to the Section Air Pollution Control)
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28 pages, 11993 KB  
Article
Transitions Between Circulation Regimes: The Role of Tropical Heating
by Ralph D. Getzandanner and David M. Straus
Atmosphere 2026, 17(2), 201; https://doi.org/10.3390/atmos17020201 - 13 Feb 2026
Viewed by 374
Abstract
Four Euro-Atlantic (EA) circulation regimes are identified using cluster analysis applied to 500 hPa geopotential heights from the ERA-Interim (ERAI) reanalysis. These are the positive and negative phases of the North Atlantic Oscillation (NAO+, NAO−), Scandinavian Blocking (SB), and the Atlantic Ridge (AR). [...] Read more.
Four Euro-Atlantic (EA) circulation regimes are identified using cluster analysis applied to 500 hPa geopotential heights from the ERA-Interim (ERAI) reanalysis. These are the positive and negative phases of the North Atlantic Oscillation (NAO+, NAO−), Scandinavian Blocking (SB), and the Atlantic Ridge (AR). This paper studies transitions between these four regimes, the signature of tropical heating preceding these transitions, and the identification of transitions for which this forcing plays a role. The findings can further our understanding of when transitions occur. To address these questions, we examine the relationship of heating to the Madden–Julian Oscillation (MJO), the El Niño Southern Oscillation (ENSO), shifts in the Intertropical Convergence Zone (ITCZ), and possible stratospheric influences. Mid-latitude diabatic heating is also examined to determine shifts in the storm tracks. We use the ERAI reanalysis to estimate diabatic heating, streamfunction, Rossby wave activity, and stratospheric zonal winds. We find that Indian Ocean tropical heating enhances the transition from the SB regime to the NAO+ regime. In contrast, western Pacific heating seems to force transitions from all other regimes into the NAO− regime. The flux of Rossby wave activity indicates that in some transitions, mid-latitudes play a role in forcing tropical heating. The majority of the transitions examined show indications of tropically forced behavior. Less than half showed evidence that mid-latitude dynamics were the primary cause of the transition. Nearly half of the transitions appeared to be related to phases of the MJO. We also found that intensification of heating in the eastern equatorial Pacific and equatorial Atlantic (ITCZ) plays a role. Transitions during the early and late parts of the season, along with the role of ENSO, are found to be modest factors. Full article
(This article belongs to the Special Issue Recent Advances in Subseasonal to Seasonal Predictability)
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18 pages, 2085 KB  
Article
Formation of Secondary Inorganic PM2.5 as Impacted by Ammonia Concentrations near an Animal Feeding Operation
by Blake Stratton, Lingjuan Wang-Li, Wei Shi, Sanjay Shah, John Classen and Kenneth Anderson
Atmosphere 2026, 17(2), 188; https://doi.org/10.3390/atmos17020188 - 11 Feb 2026
Viewed by 622
Abstract
The impact of ammonia (NH3) emissions from animal agriculture on the secondary formation of inorganic fine particulate matter (i.e., iPM2.5) has become of great public concern. The formation of iPM2.5 from NH3 is known as the gas–particle [...] Read more.
The impact of ammonia (NH3) emissions from animal agriculture on the secondary formation of inorganic fine particulate matter (i.e., iPM2.5) has become of great public concern. The formation of iPM2.5 from NH3 is known as the gas–particle partitioning of gaseous NH3 and aerosol ammonium (NH4+), which is assumed to be in a thermodynamic equilibrium. This research aimed to gain an in-depth understanding of the impact of ambient NH3 on secondary iPM2.5 by analyzing the PM2.5 mass closure, atmospheric chemical conditions, and the gas particle partitioning of NH3-NH4+ in the near field of a poultry production unit in North Carolina. Samples of precursor gases (i.e., NH3, SO2, NO2) to iPM2.5 and PM2.5 were taken on this poultry production unit at four sampling stations in four wind directions through summer, autumn and winter seasons to determine gas concentrations and PM2.5 chemical compositions. It was discovered that this rural site contained low ambient concentrations of iPM2.5 precursor gases, and PM2.5 composition was dominated by organic carbon (OC) (80% to 94%) while iPM2.5 fraction was insignificant (0% to 2%). Low availability of H2SO4 and HNO3 gases (from SO2 and NO2 conversions) limited NH3 neutralization potential and iPM2.5 formation; moreover, high OC fraction may inhibit NH4+ formation. With the field measurements of ambient temperature, humidity, precursor gases and PM2.5 chemical speciation data, the ISORROPIA-II thermodynamic equilibrium model was used to conduct the sensitivity analysis, and we found that iPM2.5 was the most sensitive to increasing total HNO3 (gas + aerosol) at low temperatures. The formation potential of iPM2.5 at this rural site was at its highest during the wintertime when SO2 was extremely low. Full article
(This article belongs to the Section Air Quality)
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18 pages, 1933 KB  
Article
Load-Dependent Efficiency and Emission Trade-Offs of n-Butanol–Diesel Blends in a Naturally Aspirated Diesel Engine
by Jaesung Kwon, Chanwoo Kang and Jongkap Ahn
Atmosphere 2026, 17(2), 182; https://doi.org/10.3390/atmos17020182 - 10 Feb 2026
Viewed by 2611
Abstract
This work systematically evaluates the combustion and emission characteristics of n-butanol–diesel blends to clarify load-dependent trade-offs. A single-cylinder diesel engine was operated under low (25%)- and high (75%)-load conditions using commercial diesel and n-butanol blends (5–15 vol%). The results indicate that n-butanol addition [...] Read more.
This work systematically evaluates the combustion and emission characteristics of n-butanol–diesel blends to clarify load-dependent trade-offs. A single-cylinder diesel engine was operated under low (25%)- and high (75%)-load conditions using commercial diesel and n-butanol blends (5–15 vol%). The results indicate that n-butanol addition tends to improve brake thermal efficiency (BTE) and reduce brake-specific energy consumption (BSEC), particularly at high loads, likely due to enhanced premixed combustion and fuel oxygenation. Emission trends exhibited distinct load-dependent behaviors: nitrogen oxides (NOx) emissions decreased at low loads, ostensibly because the charge-cooling effect of n-butanol’s high latent heat dominated, whereas they increased at high loads driven by elevated temperatures and oxygen availability. Smoke opacity, carbon monoxide (CO), and carbon dioxide (CO2) emissions were consistently reduced across all operating conditions, suggesting benefits from improved oxidation and the lower carbon content. In contrast, unburned hydrocarbon (HC) emissions increased significantly, which is primarily attributed to prolonged ignition delay and local quenching arising from the fuel’s low cetane number and high latent heat. These findings demonstrate n-butanol’s potential to enhance efficiency and mitigate smoke, CO, and CO2 emissions, though the trade-offs with HC and high-load NOx necessitate optimized control strategies. Full article
(This article belongs to the Special Issue Integrated Air Pollution Control Technology for Energy Transition (Net-Zero Emissions))
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26 pages, 8882 KB  
Article
Wildfires in the Southern Amazon: Insights into Pyro-Convective Cloud Development from Two Case Studies in August 2021
by Katyelle Ferreira da Silva Bezerra, Flavio Tiago Couto, Helber Barros Gomes, Janaína Nascimento, Paulo Vítor de Albuquerque Mendes, Dirceu Luís Herdies, Hakki Baltaci, Maria Cristina Lemos da Silva, Mayara Christine Correia Lins, Caroline Bresciani, Rafaela Lisboa Costa, Madson Tavares Silva, Heliofábio Barros Gomes, Daniel Milano Costa de Lima, José de Brito Silva, Fabrício Lopes de Araújo Paz and Fabrício Daniel dos Santos Silva
Atmosphere 2026, 17(2), 173; https://doi.org/10.3390/atmos17020173 - 6 Feb 2026
Cited by 2 | Viewed by 1169
Abstract
This study examines two wildfire events in the southern Amazon in August 2021, addressing the challenges in investigating the development of pyro-convective clouds in tropical regions. The analysis combines the Normalized Difference Vegetation Index, Fire Radiative Power derived from the Suomi-NPP and NOAA-20 [...] Read more.
This study examines two wildfire events in the southern Amazon in August 2021, addressing the challenges in investigating the development of pyro-convective clouds in tropical regions. The analysis combines the Normalized Difference Vegetation Index, Fire Radiative Power derived from the Suomi-NPP and NOAA-20 satellites, and meteorological conditions from thermodynamic profiles and atmospheric modeling. The Meso-NH model was applied exploratorily with two simulations that allow convection, at a 2.5 km resolution. In the first case, a pyro-convective cloud (PyroCu) formed directly from active fires. In the second, a deep convective cloud developed over dispersed fire hotspots, exhibiting characteristics compatible with pyro-convective activity, although uncertainties remain regarding its classification as a true PyroCb. The results indicate that background thermodynamic instability primarily controls vertical plume development, modulating the influence of fire intensity. Incorporating high-resolution thermodynamic profiles into coupled atmospheric and chemical dispersion models can improve estimates of smoke injection height, complementing information on fire power. The results provide a basis for future developments related to understanding tropical pyro-convective clouds, showing how smoke dispersion may occur in the tropical region depending on the vertical structure of the atmosphere and fire intensity. Full article
(This article belongs to the Special Issue Atmospheric Dispersion and Chemistry Models: Advances and Applications (2nd Edition))
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19 pages, 7588 KB  
Article
Characterising and Differentiating Non-Exhaust Airborne Nanoparticle Sources in Urban Traffic and Background Environments
by Yingyue Wei, George Biskos and Prashant Kumar
Atmosphere 2026, 17(2), 164; https://doi.org/10.3390/atmos17020164 - 2 Feb 2026
Viewed by 672
Abstract
The contribution of non-exhaust emissions (NEEs) to particle number concentration (PNC) remains insufficiently quantified, particularly across different urban environments. In this study, we address this gap by quantifying the contribution of NEEs to airborne nanoparticles in urban areas. Using positive matrix factorisation (PMF), [...] Read more.
The contribution of non-exhaust emissions (NEEs) to particle number concentration (PNC) remains insufficiently quantified, particularly across different urban environments. In this study, we address this gap by quantifying the contribution of NEEs to airborne nanoparticles in urban areas. Using positive matrix factorisation (PMF), conditional probability function analysis, Pearson correlation, and source identification, we identified five source factors contributing to PNC at two sites in London: a traffic site and a background site. Five source factors were resolved at both sites: Aitken-mode traffic exhaust particles, nucleation-mode exhaust emission, secondary aerosol, non-exhaust emission, and regional background accumulation. Interestingly, the contribution of NEEs differed between the two sites. At the traffic site, NEEs contributed 14.9%, while at the background site, their contribution was higher at 28.5%, likely due to the favourable summer dispersion conditions. However, the contribution of nucleation-mode exhaust emission also showed significant differences: 26.6% at the traffic site and only 9.9% at the background site. Based on these findings, we propose that air quality policies should integrate NEEs into regulations, improve road maintenance, and use PNC-based along with metal tracers to identify and control PNC. This study offers valuable insights for developing strategies to manage urban nanoparticle pollution. Full article
(This article belongs to the Section Air Quality)
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31 pages, 13397 KB  
Article
Seasonal and Diurnal Variations in Greenhouse Gas Methane (CH4) in a Rural Area of Rome (Italy)
by Antonietta Ianniello, Giulio Esposito, Cristiana Bassani, Francesca Vichi, Valerio Paolini, Walter Stefanoni, Paolo Sconocchia, Luca Tofful, Mauro Montagnoli, Andrea Imperiali, Alma Iannilli, Valentina Terenzi, Patrizio Tratzi and Emanuele Pallozzi
Atmosphere 2026, 17(2), 159; https://doi.org/10.3390/atmos17020159 - 31 Jan 2026
Viewed by 1079
Abstract
First continuous measurements of atmospheric CH4 were carried out for one year (June 2023–May 2024) at Liberti Observatory of CNR-IIA, in a semi-rural site near Rome. Seasonal and diurnal variations were analyzed. CH4 monthly mean concentrations showed maximum and minimum values [...] Read more.
First continuous measurements of atmospheric CH4 were carried out for one year (June 2023–May 2024) at Liberti Observatory of CNR-IIA, in a semi-rural site near Rome. Seasonal and diurnal variations were analyzed. CH4 monthly mean concentrations showed maximum and minimum values in winter and summer, respectively, which agree with the other European trends. Minimum CH4 values during summer could likely be due to a combination of favorable atmospheric mixing properties and increased atmospheric CH4 oxidation. The correlation analysis showed that temperature, global radiation, and wind speed revealed significant negative correlations with this greenhouse gas, indicating the influence of local sources. However, poor correlations during different seasonal periods also suggested the role of air mass transport sources. The CH4 concentrations exhibited clear diurnal cycles with daytime low and night-time high values, mainly driven by atmospheric stability conditions and photochemistry. A cluster analysis of air mass trajectories showed that CH4 concentrations were influenced all year by anthropogenic emissions. Elevated concentrations arrived from NE Europe, except in winter when the influence of NW European and local contributions became more significant. Furthermore, level-3 XCH4 data from the satellite TROPOMI showed a methane columnar concentration increase from 2018 to 2024 in agreement with the global annual increase from the NOAA network during the same period. Full article
(This article belongs to the Section Air Quality)
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17 pages, 3523 KB  
Article
Characteristics and Driving Mechanisms of Net Ecosystem Productivity in a Subtropical Moso Bamboo Forest Based on XGBoost
by Kun Zhao, Cheng Li, Huifang Liu, Xiaoyi Hua, Boxuan Duan, Manyi Li, Wenjing Chen and Chuan Jin
Atmosphere 2026, 17(2), 158; https://doi.org/10.3390/atmos17020158 - 31 Jan 2026
Cited by 1 | Viewed by 625
Abstract
As a critical agroforestry crop in Southern China, Moso bamboo, maintains regional timber security and bamboo shoot production, with its net ecosystem productivity (NEP) directly determining dry matter accumulation and economic yield. This study integrates 2024 continuous flux observations with XGBoost and SHAP [...] Read more.
As a critical agroforestry crop in Southern China, Moso bamboo, maintains regional timber security and bamboo shoot production, with its net ecosystem productivity (NEP) directly determining dry matter accumulation and economic yield. This study integrates 2024 continuous flux observations with XGBoost and SHAP explanations to characterize the subtropical bamboo forest carbon budget and its nonlinear driving mechanisms. The results show a weak carbon sink in 2024 with an annual cumulative NEP of 120 g C m−2, as high respiration of 860 g C m−2 limited organic matter conversion by consuming nearly 88% of the 980 g C m−2 total primary production. The peak production period during May and June was offset by growth stagnation in August, caused by extreme heat and drought. Net radiation served as the primary driver, with a positive contribution threshold of 75.28 W m−2, whereas precipitation exceeding 1.85 mm or air temperatures over 17.85 °C hindered carbon accumulation through radiation attenuation and metabolic heat loss. Strong radiation–precipitation interactions confirm that water’s impacts on yield are deeply contingent upon radiation backgrounds. These nonlinear regulatory pathways provide a scientific foundation for stabilizing bamboo forest productivity through synergistic water-radiation management and structural optimization during extreme climate events. Full article
(This article belongs to the Special Issue Agriculture, Ecosystems and Environment: Monitoring, Modeling and Mitigation Under Climate Change)
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20 pages, 20237 KB  
Article
Ionospheric Response to the Geomagnetic Storm of 12–14 November 2025, Based on Multi-Parameter Analysis of Data from the LAERT Topside Sounder
by Sergey Pulinets, Nadezhda Kotonaeva, Victor Depuev and Konstantin Tsybulya
Atmosphere 2026, 17(2), 150; https://doi.org/10.3390/atmos17020150 - 30 Jan 2026
Cited by 1 | Viewed by 1088
Abstract
As Akasofu noted, no two geomagnetic storms are identical, yet the storm that occurred between 12 and 14 November 2025 stands out as an exceptional phenomenon. Its impact was evident across multiple layers of the ionosphere and numerous parameters, making it essential to [...] Read more.
As Akasofu noted, no two geomagnetic storms are identical, yet the storm that occurred between 12 and 14 November 2025 stands out as an exceptional phenomenon. Its impact was evident across multiple layers of the ionosphere and numerous parameters, making it essential to conduct a comprehensive multi-parameter analysis of this event. Such an analysis relied upon data from the four LAERT topside sounders mounted aboard the recently launched Ionosfera-M satellites. Global ionospheric dynamics were thoroughlyexamined during the storm period, particularly focusing on the polar and auroral zones, along with the equatorial anomaly region. Notable features included sharp electron density gradients, widespread F-layer disturbances, and the formation of giant plasma bubbles. These elements collectively contributed to the dynamic picture of the ionospheric storm captured through multi-parameter measurements by the LAERT sounders. Full article
(This article belongs to the Special Issue Advances in Observation and Simulation Studies of Ionosphere)
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20 pages, 28396 KB  
Article
Evaluating the Effect of Emission Schemes on Dust Simulation in East Asia During Spring 2023
by Shengkai Wang, Xiao-Yi Yang and Chenghan Luo
Atmosphere 2026, 17(2), 154; https://doi.org/10.3390/atmos17020154 - 30 Jan 2026
Cited by 1 | Viewed by 888
Abstract
In the spring of 2023, dust outbreaks were unusually active in East Asia, posing substantial risks to air quality. Accurately simulating dust storms is essential for improving regional dust prediction and impact assessment. In this study, we evaluated dust simulations over East Asia [...] Read more.
In the spring of 2023, dust outbreaks were unusually active in East Asia, posing substantial risks to air quality. Accurately simulating dust storms is essential for improving regional dust prediction and impact assessment. In this study, we evaluated dust simulations over East Asia using different dust emission schemes in the FLEXDUST/FLEXPART model and quantified the regional dust budget. Overall, the GOCART (Goddard Chemistry Aerosol Radiation and Transport) scheme shows the highest skill among the evaluated schemes. Under mild dust conditions (300–1000 μg m−3), it yielded a mean PM10 bias of −89.2 μg m−3, markedly smaller than those from other schemes/models (−450.2 to −265.6 μg m−3). It also better reproduced the dominant spatial patterns of dust optical depth over Xinjiang and Inner Mongolia, with lower errors and higher correlations. Budget diagnostics show that the Taklamakan and Gobi Deserts are net dust exporters (7.4 and 11.6 Tg, respectively), whereas East Asia exhibits a negative net external flux (−12.1 Tg). The comparable magnitudes of these terms underscore the role of inter-regional transport in shaping the East Asian dust budget. These results offer insights for improving dust emission schemes in the FLEXDUST/FLEXPART model, thereby enhancing dust simulations over East Asia. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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40 pages, 3156 KB  
Review
A Review of What Can Be Learnt from Tweeks and Related Topics
by Michael J. Rycroft
Atmosphere 2026, 17(2), 152; https://doi.org/10.3390/atmos17020152 - 30 Jan 2026
Cited by 1 | Viewed by 854
Abstract
Tweeks are ELF/VLF radio signals originating from lightning discharges that exhibit dispersion due to their propagation in the Earth-ionosphere waveguide. Examples of the waveforms of tweeks and their dynamic frequency-time spectra are presented and interpreted. Tweeks observed in the daytime and night-time are [...] Read more.
Tweeks are ELF/VLF radio signals originating from lightning discharges that exhibit dispersion due to their propagation in the Earth-ionosphere waveguide. Examples of the waveforms of tweeks and their dynamic frequency-time spectra are presented and interpreted. Tweeks observed in the daytime and night-time are compared and contrasted. Tweeks observed during a solar eclipse are also discussed, as are those due to volcanic lightning and those claimed to be recorded some hours or days before a strong earthquake. The variations of tweek occurrence with season and geomagnetic activity, and with variations of solar radiation over the 11-year solar cycle, are reviewed. Wherever possible, geophysical interpretations are discussed. Theoretical models of tweek waveforms and spectra are considered; they vary according to the lightning current model used, the distance from the source (≥1 Mm), the vertical profile of ionospheric D-region ionisation and the specific mode theory used. The simplest interpretation shows that the first-order tweek cut- off frequency ~1.8 kHz is explained as reflection by the ionosphere at a height of ~83 km where the electron density is ~27 × 106 m−3. More complex interpretations are also reviewed and compared with electron density observations made by rockets and with profiles given by lower ionospheric models such as the International Reference Ionosphere or the Faraday International Reference Ionosphere. Full article
(This article belongs to the Special Issue Understanding Space Physics and Atmospheric Electricity with VLF/ELF Signals)
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20 pages, 20561 KB  
Article
The Contribution of the Thin and Dense Cloud to the Microphysical Properties of Ice Clouds over the Tibetan Plateau and Its Surrounding Regions
by Hongke Cai, Fangneng Li, Quanliang Chen, Yaqin Mao and Chong Shi
Atmosphere 2026, 17(2), 149; https://doi.org/10.3390/atmos17020149 - 29 Jan 2026
Viewed by 482
Abstract
The vertical structure and optical–microphysical properties of ice clouds determine their radiative effects. With an average altitude above 3000 m above mean sea level (AMSL) and unique thermal circulation, the Tibetan Plateau forms ice clouds with seasonally varying microphysical characteristics. In this study, [...] Read more.
The vertical structure and optical–microphysical properties of ice clouds determine their radiative effects. With an average altitude above 3000 m above mean sea level (AMSL) and unique thermal circulation, the Tibetan Plateau forms ice clouds with seasonally varying microphysical characteristics. In this study, satellite lidar observations from CALIPSO and ERA5 reanalysis from 2006 to 2023 reveal significant seasonal variation in ice clouds over the Tibetan Plateau and adjacent regions. In winter, maximums of the backscatter coefficient (β532) and ice water content (IWC) were found south of the Qinling-Huaihe Line, as well as in the Sichuan Basin and the Yangtze Plain. In summer, these maximums move onto the Plateau, and the cloud height rises by about 1 km. The altitude of the β532 maximum rises from about 4 km in winter to nearly 6 km in summer. Among four cloud categories defined by joint geometric and optical thickness thresholds, clouds with small geometric thickness and large optical thickness (thin and dense clouds) are the most radiatively important. While these clouds are seldom observed over the Tibetan Plateau in winter, they contribute to over thirty percent of local ice cloud occurrences during summer. Their preferred altitude rises from 3–4 km to 6–7 km, occurring under comparatively warmer environmental temperatures. Although limited in geometric depth, the thin and dense clouds exhibit the highest β532 and IWC, the lowest multiple scattering coefficient (η532), and the highest depolarization ratio (δ532). They contribute about thirty percent of the total extinction and backscatter, despite representing only ten to twenty percent of all cases. Full article
(This article belongs to the Section Meteorology)
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29 pages, 7143 KB  
Article
Observation-Based Reconstruction of High-Resolution Daily Temperature Field Using Lapse-Rate-Constrained Kriging in Complex Terrain: A Nationwide Dataset for South Korea
by Youjeong Youn, Menas Kafatos, Seung Hee Kim and Yangwon Lee
Atmosphere 2026, 17(2), 148; https://doi.org/10.3390/atmos17020148 - 29 Jan 2026
Cited by 1 | Viewed by 896
Abstract
High-resolution air-temperature fields are essential for climate, hydrologic, and ecological applications in complex terrain, yet operational products often lack the spatial detail to resolve topographic effects. We develop an observation-driven reconstruction of daily air temperature fields for South Korea (2024) using ordinary kriging [...] Read more.
High-resolution air-temperature fields are essential for climate, hydrologic, and ecological applications in complex terrain, yet operational products often lack the spatial detail to resolve topographic effects. We develop an observation-driven reconstruction of daily air temperature fields for South Korea (2024) using ordinary kriging with lapse-rate correction (OKLR), integrating a dense network of over 500 stations from the Automatic Mountain Meteorology Observation System (AMOS) and the Automated Surface Observing System (ASOS). The OKLR framework systematically removes elevation-driven trends using a physically based fixed lapse rate (–6.5 °C km−1), performs kriging on detrended residuals, and reapplies Digital Elevation Model (DEM)-based corrections to generate high-fidelity daily fields at a 270 m grid spacing. Unlike numerical weather prediction (NWP) models that simulate atmospheric processes, this approach reconstructs spatially continuous fields directly from dense in situ observations, ensuring empirical grounding. Extensive daily spatial cross-validation (n = 37,813) demonstrates that OKLR (MAE = 0.656 °C) significantly outperforms elevation-unadjusted ordinary kriging by ≈37% and the operational 1.5 km LDAPS product (MAE = 0.895 °C) by 27%. This performance gain is particularly pronounced in high-elevation zones (>700 m) and natural surfaces (≈73% of the study area), where topographic complexity is greatest. The final observation-constrained reconstruction attains a robust MAE of 0.462 °C with near-zero bias over 188,318 station–days. As the first nationwide daily temperature dataset for South Korea at 270 m resolution, this study provides a critical foundation for precision agriculture, ecosystem monitoring, and climate change adaptation in topographically diverse environments. Full article
(This article belongs to the Section Meteorology)
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20 pages, 3087 KB  
Article
Catalytic Combustion Characteristics for Removal of High-Concentration Volatile Organic Compounds (VOCs)
by Tae-Jin Kang, Hyun-Ji Kim, Jieun Lee, Jin-Hee Lee, Hyo-Sik Kim, Jin-Ho Kim, No-Kuk Park, Soo Chool Lee and Suk-Hwan Kang
Atmosphere 2026, 17(2), 137; https://doi.org/10.3390/atmos17020137 - 27 Jan 2026
Viewed by 897
Abstract
The conventional treatment of high-concentration volatile organic compounds (VOCs) relies on energy-intensive dilution to avoid explosion risks. This study proposes an efficient catalytic combustion process treating VOCs directly within the explosive range while recovering reaction heat using Pt/γ-Al2O3-based catalysts [...] Read more.
The conventional treatment of high-concentration volatile organic compounds (VOCs) relies on energy-intensive dilution to avoid explosion risks. This study proposes an efficient catalytic combustion process treating VOCs directly within the explosive range while recovering reaction heat using Pt/γ-Al2O3-based catalysts promoted with La and Ce. Catalysts (0.05–0.5 wt% Pt) were synthesized via impregnation and characterized using FE-SEM, BET, and XRD. Catalytic combustion experiments at VOC concentrations up to 13,000 ppm showed combustion initiation below 200 °C, achieving 83–99% conversions at 300 °C with complete oxidation to CO2. Although 5 vol.% moisture significantly inhibited low-temperature activity through competitive adsorption, La and Ce promoters (10 wt%) effectively overcame this limitation by increasing surface area (up to 194.93 m2/g) and oxygen mobility. The Ce-promoted catalyst demonstrated superior water tolerance, achieving complete conversion at 200–210 °C due to its high Oxygen Storage Capacity (OSC). Bench-scale validation using a 1 Nm3/h system confirmed industrial feasibility. Operating at 220 °C with 13,000 ppm toluene for 100 h, the catalyst maintained >99.98% conversion with negligible deactivation and THC emissions below 2 ppm. The double-jacket heat exchanger effectively managed reaction heat (limiting temperature rise to ~20 °C) and recovered it as steam. Compared to Regenerative Thermal Oxidation, this Regenerative Catalytic Oxidation approach reduced emissions and energy consumption. This work demonstrates a robust “combustion-with-recovery” strategy for high-concentration VOC treatment, offering a sustainable alternative with high efficiency, stability, and safe energy-integrated operation. Full article
(This article belongs to the Special Issue Emissions of Volatile Organic Compounds (VOCs): Characterization, Environmental Impacts and Control)
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18 pages, 2986 KB  
Article
Comparing Statistical and Machine-Learning Models for Seasonal Prediction of Atlantic Hurricane Activity
by Xiaoran Chen and Lian Xie
Atmosphere 2026, 17(2), 129; https://doi.org/10.3390/atmos17020129 - 26 Jan 2026
Cited by 1 | Viewed by 761
Abstract
Tropical cyclones pose major risks to life and property, especially as coastal populations grow and climate change increases the likelihood of intense storms, making seasonal prediction of tropical cyclones an important scientific and societal goal. This study uses HURDAT best-track records from 1950 [...] Read more.
Tropical cyclones pose major risks to life and property, especially as coastal populations grow and climate change increases the likelihood of intense storms, making seasonal prediction of tropical cyclones an important scientific and societal goal. This study uses HURDAT best-track records from 1950 to 2024 to quantify annual tropical cyclone, hurricane, and major hurricane counts across the Atlantic basin, Caribbean Sea, and Gulf of Mexico. These nine targets are paired with 34 monthly climate predictors from NOAA and NASA GISS—including SST and ENSO indices, Main Development Region (MDR) wind and pressure fields, and latent heat flux empirical orthogonal functions—evaluated under nine predictor-set configurations. Four forecasting approaches were developed and tested under operationally realistic conditions—Lasso regression, K-nearest neighbors (KNN), an artificial neural network (ANN), XGBoost—using a 30-year sliding-window cross-validation design and a Poisson log-likelihood skill score relative to climatology. Lasso performs reliably with concise, physically interpretable predictors, while XGBoost provides the most consistent overall skill, particularly for basin-wide total cyclone and hurricane counts. The skill of ANN is limited by small sample sizes, and KNN offers only marginal improvements. Forecast skill is the highest for basin-wide storm totals and decreases for regional major-hurricane targets due to lower event frequencies and stronger predictability limits. Full article
(This article belongs to the Special Issue Machine Learning for Atmospheric and Remote Sensing Research)
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19 pages, 5547 KB  
Article
Multiscale Analysis of Drought Characteristics in China Based on Precipitable Water Vapor and Climatic Response Mechanisms
by Ruohan Liu, Qiulin Dong, Lv Zhou, Fei Yang, Yue Sun, Yanru Yang and Sicheng Zhang
Atmosphere 2026, 17(2), 119; https://doi.org/10.3390/atmos17020119 - 23 Jan 2026
Viewed by 406
Abstract
Droughts are recognized as one of the most devastating extreme climate events, leading to severe socioeconomic losses and ecological degradation globally under climate change. With global warming, the frequency and intensity of extreme droughts are increasing, posing critical challenges to water resource management. [...] Read more.
Droughts are recognized as one of the most devastating extreme climate events, leading to severe socioeconomic losses and ecological degradation globally under climate change. With global warming, the frequency and intensity of extreme droughts are increasing, posing critical challenges to water resource management. The Standardized Precipitation Conversion Index (SPCI) has demonstrated potential in drought monitoring; however, its applicability across diverse climatic zones and multiple temporal scales remains inadequately validated. This study addresses this gap by establishing a novel multi-scale inversion analysis using ERA5-based precipitable water vapor (PWV) and precipitation data. SPCI is selected for its advantage in eliminating climatic background biases through probability normalization, overcoming limitations of traditional indices such as the Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI). We systematically evaluated the spatiotemporal evolution of Precipitation Efficiency (PE) and SPCI across four climatic zones in China. Results show that the first two principal components explain over 85% of the spatiotemporal variability of PE, with PC1 independently contributing from 82.05% to 83.80%. This high variance contribution underscores that the spatiotemporal patterns of PE are dominated by a few key climatic drivers, validating the robustness of the principal component analysis. SPCI exhibits strong correlation with SPI, exceeding 0.95 in the Tropical Monsoon Zone (TMZ) at scales of 1–6 months, indicating its utility for short-to-medium-term drought monitoring. Distinct zonal differentiation in PE patterns is revealed, such as the bimodal annual cycle in the Tropical-Subtropical Monsoon Composite Zone (TSMCZ). This study evaluates the performance of the SPCI against the widely used SPI and SPEI across four major climatic zones in China. It validates the SPCI’s applicability across China’s complex climates, providing a scientific basis for region-specific drought early warning and water resource optimization. Full article
(This article belongs to the Special Issue Meteorological Models: Recent Trends, Current Progress and Future Directions (2nd Edition))
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34 pages, 1419 KB  
Article
Load-Dependent Shipping Emission Factors Considering Alternative Fuels, Biofuels and Emission Control Technologies
by Achilleas Grigoriadis, Theofanis Chountalas, Evangelia Fragkou, Dimitrios Hountalas and Leonidas Ntziachristos
Atmosphere 2026, 17(2), 122; https://doi.org/10.3390/atmos17020122 - 23 Jan 2026
Viewed by 1012
Abstract
Shipping is a high-energy-intensive sector and a major source of climate-relevant and harmful air pollutant emissions. In response to growing environmental concerns, the sector has been subject to increasingly stringent regulations, promoting the uptake of alternative fuels and emission control technologies. Accurate and [...] Read more.
Shipping is a high-energy-intensive sector and a major source of climate-relevant and harmful air pollutant emissions. In response to growing environmental concerns, the sector has been subject to increasingly stringent regulations, promoting the uptake of alternative fuels and emission control technologies. Accurate and diverse emission factors (EFs) are critical for quantifying shipping’s contribution to current emission inventories and projecting future developments under different policy scenarios. This study advances the development of load-dependent EFs for ships by incorporating alternative fuels, biofuels and emission control technologies. The methodology combines statistical analysis of data from an extensive literature review with newly acquired on-board emission measurements, including two-stroke propulsion engines and four-stroke auxiliary units. To ensure broad applicability, the updated EFs are expressed as functions of engine load and are categorized by engine and fuel type, covering conventional marine fuels, liquified natural gas, methanol, ammonia and biofuels. The results provide improved resolution of shipping emissions and insights into the role of emission control technologies, supporting robust, up-to-date emission models and inventories. This work contributes to the development of effective strategies for sustainable maritime transport and supports both policymakers and industry stakeholders in their decarbonization efforts. Full article
(This article belongs to the Special Issue Air Pollution from Shipping: Measurement and Mitigation)
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21 pages, 10072 KB  
Article
Model Intercomparison and Resolution Dependence in Real-Time Numerical Air Quality Forecasting over North China
by Zijian Jiang, Zhiyin Zou, Wending Wang, Huansheng Chen, Zichen Wu, Xueshun Chen and Zhe Wang
Atmosphere 2026, 17(2), 123; https://doi.org/10.3390/atmos17020123 - 23 Jan 2026
Viewed by 520
Abstract
High-resolution air quality models (AQMs) are critical for real-time air quality forecasting and exposure assessment, although their computational costs increase cubically with resolution. Quantifying model sensitivity to resolution is therefore crucial for developing effective forecasting systems. This study conducts a systematic model intercomparison [...] Read more.
High-resolution air quality models (AQMs) are critical for real-time air quality forecasting and exposure assessment, although their computational costs increase cubically with resolution. Quantifying model sensitivity to resolution is therefore crucial for developing effective forecasting systems. This study conducts a systematic model intercomparison of three widely used AQMs (CAMx, CMAQ, NAQPMS) under identical input conditions at 45, 15, and 5 km resolutions to forecast PM2.5 and O3 in the North China Plain during 2021. Results indicate distinct, model-dependent responses to grid refinement. NAQPMS achieves the optimal PM2.5 forecasting performance at 5 km, with improvements in nearly all evaluated statistics. CMAQ excels in O3 prediction at 5 km resolution, with RMSE reducing 6.48 μg/m3 relative to the coarsest grids. We also found that terrain complexity significantly influences these resolution-dependent biases, leading to a substantial 19.51% reduction in NMB in the CAMx PM2.5 simulation over mountain areas. Moreover, the evaluation of 10-day forecasting accuracy suggests that a high-resolution setting is recommended for NAQPMS and CMAQ, whereas a coarser resolution is sufficient for CAMx. These findings underscore that optimizing real-time forecasting strategies requires a critical investigation of inter-model physicochemical discrepancies rather than universally pursuing higher resolution. Full article
(This article belongs to the Special Issue Secondary Atmospheric Pollution Formations and Its Precursors)
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32 pages, 7360 KB  
Article
Analysis of Air Pollution in the Orontes River Basin in the Context of the Armed Conflict in Syria (2019–2024) Using Remote Sensing Data and Geoinformation Technologies
by Aleksandra Nikiforova, Vladimir Tabunshchik, Elena Vyshkvarkova, Roman Gorbunov, Tatiana Gorbunova, Anna Drygval, Cam Nhung Pham and Andrey Kelip
Atmosphere 2026, 17(1), 115; https://doi.org/10.3390/atmos17010115 - 22 Jan 2026
Viewed by 655
Abstract
Rapid urbanization and anthropogenic activities have led to a significant deterioration of air quality, adversely affecting human health and ecosystems. The study of transboundary river basins, where air pollution is exacerbated by political and socio-economic factors, is of particular relevance. This paper presents [...] Read more.
Rapid urbanization and anthropogenic activities have led to a significant deterioration of air quality, adversely affecting human health and ecosystems. The study of transboundary river basins, where air pollution is exacerbated by political and socio-economic factors, is of particular relevance. This paper presents the results of an analysis of the spatiotemporal distribution of pollutants (Aerosol Index (AI), Methane (CH4), Carbon Monoxide (CO), Formaldehyde (HCHO), Nitrogen Dioxide (NO2), Ozone (O3), Sulfur Dioxide (SO2)) in the ambient air within the Orontes River basin across Lebanon, Syria, and Turkey for the period 2019–2024. The research is based on satellite monitoring data (Copernicus Sentinel-5P), processed using the Google Earth Engine (GEE) cloud-based platform and GIS technologies (ArcGIS 10.8). The dynamics of population density (LandScan) and the impact of military operations in Syria on air quality were additionally analyzed using media content analysis. The results showed that the highest concentrations of pollutants were recorded in Syria, which is associated with the destruction of infrastructure, military operations, and unregulated emissions. The main sources of pollution were: explosions, fires, and destruction during the conflict (aerosols, CO, NO2, SO2); methane (CH4) leaks from damaged oil and gas facilities; the use of low-quality fuels and waste burning. Atmospheric circulation contributed to the eastward transport of pollutants, minimizing their spread into Lebanon. Population density dynamics are related to changes in concentrations of pollutants (e.g., nitrogen dioxide). The results of the study highlight the need for international cooperation to monitor and reduce air pollution in transboundary regions, especially in the context of armed conflicts. The obtained data can be used to develop measures to improve the environmental situation and protect public health. Full article
(This article belongs to the Special Issue Study of Air Pollution Based on Remote Sensing (2nd Edition))
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18 pages, 26343 KB  
Article
Wind Analysis of Typhoon Jebi (T1821) Based on High-Resolution WRF-LES Simulation
by Tao Tao, Bingjian Hao, Jinbo Zheng and Qingsong Zhang
Atmosphere 2026, 17(1), 110; https://doi.org/10.3390/atmos17010110 - 21 Jan 2026
Cited by 1 | Viewed by 560
Abstract
This study investigates the performance of a high-resolution Weather Research and Forecasting with large-eddy simulation (WRF-LES) model in simulating the strong wind of a realistic typhoon (Jebi, 2018). Multiple domains are nested to downscale the grid resolution from 4.5 km to 33.3 m, [...] Read more.
This study investigates the performance of a high-resolution Weather Research and Forecasting with large-eddy simulation (WRF-LES) model in simulating the strong wind of a realistic typhoon (Jebi, 2018). Multiple domains are nested to downscale the grid resolution from 4.5 km to 33.3 m, and grid size sensitivity is tested in the innermost WRF-LES domain. The commonly used 1.5-order turbulent kinetic energy (TKE) subgrid-scale (SGS) model is excessively dissipative near the ground; this causes overshoot in the mean velocity profile compared with the expected log-law profile, a phenomenon slightly amplified by finer grids. Horizontal roll structures in the typhoon boundary can be effectively resolved with the 100 m horizontal grid size (Δx). However, higher resolution is needed to capture small-scale turbulence, and the effective mesh resolution for resolved turbulence is about 5–9Δx near the ground. The nonlinear backscatter and anisotropy (NBA) model significantly reduces the overshoot, and the resolved velocity structures are insensitive to the SGS model except for the lowest model level. Full article
(This article belongs to the Special Issue Advances in Computational Wind Engineering and Wind Energy (2nd Edition))
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31 pages, 16797 KB  
Article
Synoptic Ocean–Atmosphere Coupling at the Intertropical Convergence Zone and Its Vicinity in the Western Tropical Atlantic Ocean
by Breno Tramontini Steffen, Ronald Buss de Souza, Rose Ane Pereira de Freitas, Mauricio Almeida Noernberg and Claudia Klose Parise
Atmosphere 2026, 17(1), 101; https://doi.org/10.3390/atmos17010101 - 18 Jan 2026
Viewed by 733
Abstract
In the Atlantic Ocean, the Intertropical Convergence Zone (ITCZ) sustains the climate of northeastern Brazil and northwestern Africa by modulating their rainy and dry seasons. Using observational data, radiosondes and Expendable Bathythermographs (XBTs), we investigated short-term ocean–atmosphere coupling across the ITCZ region along [...] Read more.
In the Atlantic Ocean, the Intertropical Convergence Zone (ITCZ) sustains the climate of northeastern Brazil and northwestern Africa by modulating their rainy and dry seasons. Using observational data, radiosondes and Expendable Bathythermographs (XBTs), we investigated short-term ocean–atmosphere coupling across the ITCZ region along the 38° W meridian. The data represents synchronous measurements of the marine atmospheric boundary layer (MABL) and the ocean’s mixed layer (OML) for the period between 17 October and 8 November 2018. The ITCZ demonstrated pronounced variability in position, intensity, and width, driven by the changes in the predominance of northeast and southeast trade winds. These atmospheric changes directly impacted the Equatorial Divergence (ED), which transitioned from an asymmetric structure with shallower isothermal layer depths (ILDs) (~−14 m) around 11° N to a more homogenous region between 5° N and 10° N, with an average ILD of −21.83 ± 5.23 m. A comparison with ORAS5 and WOA23 indicates that the products reproduce the vertical thermal structure of the WTAO well (r2 > 0.9) but systematically overestimate the temperature at the bottom of the ILD by 3–4 °C. The difference between the ILD and the mixed layer depth (MLD) is more pronounced south of the ED due to the Amazon River salinity front, advected by the NECC, but the ILD estimated from XBT data closely matches the MLD estimated for ORAS5 and WOA23 in the ED region. These unprecedented observations showcase, for the first time, short-term ocean–atmosphere coupled variability across the WTAO ITCZ region, highlighting the importance of atmospheric synoptic-scale processes in modulating the OML and the ED. Full article
(This article belongs to the Special Issue Physical Interactions Between Ocean-Atmosphere Boundary Layers from Turbulent to Climate Scales)
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20 pages, 657 KB  
Review
A Critical Analysis of Agricultural Greenhouse Gas Emission Drivers and Mitigation Approaches
by Yezheng Zhu, Yixuan Zhang, Jiangbo Li, Yiting Liu, Chenghao Li, Dandong Cheng and Caiqing Qin
Atmosphere 2026, 17(1), 97; https://doi.org/10.3390/atmos17010097 - 17 Jan 2026
Viewed by 959
Abstract
Agricultural activities are major contributors to global greenhouse gas (GHG) emissions, with methane (CH4) and nitrous oxide (N2O) emissions accounting for 40% and 60% of total agricultural emissions, respectively. Therefore, developing effective emission reduction pathways in agriculture is crucial [...] Read more.
Agricultural activities are major contributors to global greenhouse gas (GHG) emissions, with methane (CH4) and nitrous oxide (N2O) emissions accounting for 40% and 60% of total agricultural emissions, respectively. Therefore, developing effective emission reduction pathways in agriculture is crucial for achieving carbon budget balance. This article synthesizes the impact of farmland management practices on GHG emissions, evaluates prevalent accounting methods and their applicable scenarios, and proposes mitigation strategies based on systematic analysis. The present review (2000–2025) indicates that fertilizer management dominates research focus (accounting for over 50%), followed by water management (approximately 18%) and tillage practices (approximately 14%). Critically, the effects of these practices extend beyond GHG emissions, necessitating concurrent consideration of crop yields, soil health, and ecosystem resilience. Therefore, it is necessary to conduct joint research by integrating multiple approaches such as water-saving irrigation, conservation tillage and intercropping of leguminous crops, so as to enhance productivity and soil quality while reducing emissions. The GHG accounting framework and three primary accounting methods (In situ measurement, Satellite remote sensing, and Model simulation) each exhibit distinct advantages and limitations, requiring scenario-specific selection. Further refinement of these methodologies is imperative to optimize agricultural practices and achieve meaningful GHG reductions. Full article
(This article belongs to the Special Issue Gas Emissions from Soil)
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20 pages, 2875 KB  
Article
Characteristics and Sources of Particulate Matter During a Period of Improving Air Quality in Urban Shanghai (2016–2020)
by Xinlei Wang, Zheng Xiao, Lian Duan and Guangli Xiu
Atmosphere 2026, 17(1), 99; https://doi.org/10.3390/atmos17010099 - 17 Jan 2026
Viewed by 487
Abstract
Following the implementation of the Shanghai Clean Air Act, this study investigates the evolution of air pollution in central Shanghai (Putuo District) by analyzing continuous monitoring data (2016–2020) and chemical speciation of particulate matter (2017–2018). The results confirm a transition toward a “low [...] Read more.
Following the implementation of the Shanghai Clean Air Act, this study investigates the evolution of air pollution in central Shanghai (Putuo District) by analyzing continuous monitoring data (2016–2020) and chemical speciation of particulate matter (2017–2018). The results confirm a transition toward a “low exceedance rate and low background concentration” regime. However, short-term exceedance episodes persist, generally occurring in winter and spring, with significantly amplified diurnal variations on exceedance days. Distinct patterns emerged between PM fractions: PM10 exceedances were characterized by a single morning peak linked to traffic-induced coarse particles, while PM2.5 exceedances showed synchronized diurnal peaks with NO2, suggesting a stronger contribution from vehicle exhaust. Source apportionment revealed that mineral components (21.61%) and organic matter (OM, 21.02%) dominated in PM10, implicating construction and road dust. In contrast, PM2.5 was primarily composed of OM (26.73%) and secondary inorganic ions (dominated by nitrate), highlighting the greater importance of secondary formation. The findings underscore that sustained PM2.5 mitigation requires targeted control of gasoline vehicle emissions and gaseous precursors. 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)
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17 pages, 5416 KB  
Article
Dynamic Ocean–Atmosphere Processes of Typhoon Chan-Hom and Their Impact on Intensity, Rainfall and SST Cooling
by Guiting Song, Venkata Subrahmanyam Mantravadi, Chen Wang, Xiaoqing Liao, Yanmei Li and Shahriyor Nurulloyev
Atmosphere 2026, 17(1), 91; https://doi.org/10.3390/atmos17010091 - 16 Jan 2026
Viewed by 789
Abstract
This study aims to investigate the effects of Chan-Hom (2015) typhoon-induced variations in enthalpy flux (EF) and moisture flux (MF) on intensity variations and rainfall. Chan-Hom (2015) made landfall at Zhoushan, then changed its direction and moved towards Korea. This analysis used ERA5 [...] Read more.
This study aims to investigate the effects of Chan-Hom (2015) typhoon-induced variations in enthalpy flux (EF) and moisture flux (MF) on intensity variations and rainfall. Chan-Hom (2015) made landfall at Zhoushan, then changed its direction and moved towards Korea. This analysis used ERA5 reanalyzed data, encompassing daily surface latent and sensible heat flux, along with wind measurements at a height of 10 m. Furthermore, wind components and specific humidity data from the 1000–200 hPa level in ERA5 were utilized to compute the MF and MF convergence, in accordance with the equations outlined in the methodology. This study examines the correlation among typhoon intensity, precipitation, MF, and EF. The mechanism by which Typhoon Chan-Hom has caused a decline in sea surface temperature (SST) was analyzed. Typhoons need a higher EF that can affect them before landfall to maintain their intensity. The highest LHF was observed (340 W/m2) prior to typhoon landfall, indicating that LHF responds to intensity-induced wind during Chan-Hom. Typhoon-induced rainfall is mainly controlled by the MF convergence, rather than the typhoon intensity. The spatial and temporal distributions of MF and MF convergence (MFC) during typhoon formation to landfall reveal that the symmetric MFC is dominated by typhoon intensity; a symmetrical structure is observed when the intensity is high. MFC includes wind convergence and moisture advection. Wind convergence dominates the MFC during typhoons, but moisture advection forms at the eyewall. MF during the typhoon’s landfall can relate to the amount of rainfall that occurred over the land. However, the rainfall pattern changed after landfall, and the typhoon changed its direction. SST cooling observed in the study area is mainly due to the upwelling process with strong cyclonic winds. Full article
(This article belongs to the Special Issue Ocean–Atmosphere–Land Interactions and Their Roles in Climate Change (2nd Edition))
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