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Atmosphere
Volume 16
Issue 1
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Atmosphere, Volume 16, Issue 1 (January 2025) – 113 articles

Cover Story (view full-size image): Standardized and high-precision measurements of greenhouse gases (GHGs) such as carbon dioxide (CO2) and methane (CH4) are of pivotal importance in the effort to determine short- and long-term trends in atmosphere quality. In Europe, atmospheric observatories are not equally distributed in the northern and southern regions of the continent, and southern areas are affected by notable gaps in the distribution of such stations. The new Potenza Class 1 station is now being constructed to expand existing Integrated Carbon Observation System (ICOS) research infrastructure. In this research paper, the characteristics of the site, together with the infrastructural and instrumental setups of the new ICOS POT station, are presented. We also discuss the results of preliminary CO2 and CH4 measurements performed during a summer campaign. View this paper
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21 pages, 2363 KiB  
Article
Assessing the COVID-19 Lockdown Impact on Global Air Quality: A Transportation Perspective
by Meina Zheng, Feng Liu and Meichang Wang
Atmosphere 2025, 16(1), 113; https://doi.org/10.3390/atmos16010113 - 20 Jan 2025
Viewed by 448
Abstract
To address the COVID-19 pandemic, governments worldwide implemented mandatory restrictions. As an unintended consequence of these responses, significant air pollution reductions have been recorded across the world. We provide cross-national evidence on the causal impact of pandemic-induced lockdowns on air quality. Using daily [...] Read more.
To address the COVID-19 pandemic, governments worldwide implemented mandatory restrictions. As an unintended consequence of these responses, significant air pollution reductions have been recorded across the world. We provide cross-national evidence on the causal impact of pandemic-induced lockdowns on air quality. Using daily air pollution data between 1 January and 31 December 2020, covering 596 major cities in 77 countries, we analyzed the data with a generalized difference-in-differences approach. The results show that lockdown restrictions reduced global concentrations of NO2 by 21~35%, PM10 by 14~26%, PM2.5 by 9~18%, CO by 6~16%, and SO2 by 5~16%, while the O3 concentrations increased by 15~29% under eight specific lockdown measures. Furthermore, a simultaneous equations model suggests that reductions in public and private mobility, measured by changes in public transportation and car ridership, partly explain the observed decreases in air pollution. These findings have significant implications for ongoing global efforts to mitigate air pollution and underscore the pivotal role of public transit in achieving this goal. Full article
(This article belongs to the Section Air Quality and Health)
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15 pages, 2706 KiB  
Article
Estimating the Contribution of the Summer Traffic Peak to PM2.5, NOx, and NMVOCs
by Petra Dolšak Lavrič and Andreja Kukec
Atmosphere 2025, 16(1), 112; https://doi.org/10.3390/atmos16010112 - 20 Jan 2025
Viewed by 408
Abstract
Air quality is becoming an important asset of modern society. Europe is adopting regulations that will enable better air quality for residents and encourage detailed study of emissions sources. Transport is recognized as a flourishing sector with the yearly growth of vehicle numbers. [...] Read more.
Air quality is becoming an important asset of modern society. Europe is adopting regulations that will enable better air quality for residents and encourage detailed study of emissions sources. Transport is recognized as a flourishing sector with the yearly growth of vehicle numbers. Even if the transport emissions trend slightly decreases, there is a concern that the increase in vehicle numbers on the road will slow down the process. Data from the bottom-up approach, estimating emissions from transit vehicles and tourism activities, was identified as a critical knowledge gap. Our study identifies and evaluates the issue of vehicle congestion on the roads during the summer, primarily driven by transit demands and tourism activities. The methodology to capture an understanding of traffic-related emissions from the summer vehicle peak was developed. Summer traffic peak was estimated by comparing the summer vehicle numbers with those of other parts of the year. Vehicle numbers were recognized by vehicle counters located on a Slovenian highway junction in the year 2021. Moreover, the study also revealed the emissions from the summer traffic peak, calculated by the COPERT emission model. We observed that, on an average summer day, there are up to 11,520 additional vehicles on Slovenian roads. It was estimated that the peak in summer passenger cars contributes up to 41,875 kg, 9542 kg, and 3057 kg of NOx, NMVOCs, and PM2.5 emissions. The maximum emissions of NOx and PM2.5 from light duty vehicles are 17,108 kg and 867 kg. There are non-negligible emissions of NMVOCs from motorcycles and these represent up to 3042 kg. Full article
(This article belongs to the Special Issue Particulate Matters in Ambient Air: Characteristics, Composition, and Sources)
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17 pages, 5474 KiB  
Article
Research on Typhoon Prediction by Integrating Numerical Simulation and Deep Learning Methods
by Tianyi Lv, Huaming Yu, Liangshi Lin, Yijun Tao and Xin Qi
Atmosphere 2025, 16(1), 111; https://doi.org/10.3390/atmos16010111 - 20 Jan 2025
Viewed by 453
Abstract
Typhoons rank among the most destructive natural disasters, significantly affecting human activities and daily life. Atmospheric numerical model wind fields, which are widely utilized, often underestimate typhoon intensity. This study proposes a model for predicting typhoon maximum wind speeds using the Long Short-Term [...] Read more.
Typhoons rank among the most destructive natural disasters, significantly affecting human activities and daily life. Atmospheric numerical model wind fields, which are widely utilized, often underestimate typhoon intensity. This study proposes a model for predicting typhoon maximum wind speeds using the Long Short-Term Memory (LSTM) neural network. The model predicts maximum wind speeds based on existing atmospheric numerical forecasts, constructs a parametric wind field model from these predictions, and integrates it with the numerical model wind fields to generate an LSTM-optimized wind field. The results show that the LSTM model accurately predicts typhoon maximum wind speeds, with the predicted extreme values closely aligning with actual observations and capturing the trends of maximum wind speed variations. Compared with the ERA5 typhoon maximum wind speed, the C of the LSTM model for predicting the typhoon maximum wind speed is improved from 0.801 to 0.859, and the RMSE and MAE are reduced by 58% and 64%, respectively. In the simulation of Typhoon DELTA (2020), the LSTM-optimized wind field exhibits substantially higher wind speed intensities in the central region of the typhoon compared to the ERA5 wind field, providing a more accurate representation of the intensity and structure of the typhoon. Full article
(This article belongs to the Section Meteorology)
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20 pages, 5107 KiB  
Article
Temporal and Spatial Assessment of Glacier Elevation Change in the Kangri Karpo Region Using ASTER Data from 2000 to 2024
by Qihua Wang, Yuande Yang, Jiayu Hu, Jianglong Zhang, Zuqiang Li and Yuechen Wang
Atmosphere 2025, 16(1), 110; https://doi.org/10.3390/atmos16010110 - 19 Jan 2025
Viewed by 487
Abstract
Temperate glaciers in the Kangri Karpo region of the southeastern Qinghai–Tibet Plateau (QTP) have experienced significant ablation in recent decades, increasing the risk of glacier-related hazards and impacting regional water resources. However, the spatial and temporal pattern of mass loss in these glaciers [...] Read more.
Temperate glaciers in the Kangri Karpo region of the southeastern Qinghai–Tibet Plateau (QTP) have experienced significant ablation in recent decades, increasing the risk of glacier-related hazards and impacting regional water resources. However, the spatial and temporal pattern of mass loss in these glaciers remains inadequately quantified. In this study, we used ASTER L1A stereo images to construct a high-resolution elevation time series and provide a comprehensive spatial–temporal assessment of glacier elevation change from 2000 to 2024. The results indicate that almost all glaciers have experienced rapid ablation, with an average surface elevation decrease of −18.35 ± 5.13 m, corresponding to a rate of −0.76 ± 0.21 m yr−1. Glaciers in the region were divided into the northern and southern basins, with average rates of −0.79 ± 0.17 m yr−1 and −0.72 ± 0.13 m yr−1, respectively. A notable difference in acceleration trends between the two basins was observed, with the elevation rate increasing from −0.78 ± 0.17m yr−1 to −1.04 ± 0.17 m yr−1 and from −0.52 ± 0.13 m yr−1 to −0.92 ± 0.13 m yr−1, respectively. The seasonal cycle was identified in glacier surface elevation change, with an accumulation period from November to March followed by a prolonged ablation period. The seasonal amplitude decreased with elevation, with higher elevations exhibiting longer accumulation periods and less ablation. Correlation analysis with meteorological data indicated that higher summer temperatures and increased summer rainfall intensify elevation loss, while increased spring snowfall may reduce ablation. Our analysis highlights distinct variations in glacier elevation changes across different locations, elevations, and climatic conditions in the Kangri Karpo region, providing valuable insights into glacier responses to environmental changes on the Tibetan Plateau. Full article
(This article belongs to the Special Issue Analysis of Global Glacier Mass Balance Changes and Their Impacts)
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14 pages, 3024 KiB  
Article
Differential Susceptibility to Particulate Matter-Induced Cardiac Remodeling and Senescence: A Comparative Study in Young and Aged Mice
by Dunia Waked, Gabriel Henrique Rodella Guedes, Raissa Macedo, Paulo Hilário Nascimento Saldiva, Mariana Matera Veras and Ana Paula Cremasco Takano
Atmosphere 2025, 16(1), 109; https://doi.org/10.3390/atmos16010109 - 19 Jan 2025
Viewed by 429
Abstract
Background: Epidemiological and toxicological studies have shown that inhalation of particulate matter (PM), a major component of air pollution, is associated with the development of cardiovascular diseases (CVDs). Cellular senescence and other aging mechanisms are also key factors in the development and progression [...] Read more.
Background: Epidemiological and toxicological studies have shown that inhalation of particulate matter (PM), a major component of air pollution, is associated with the development of cardiovascular diseases (CVDs). Cellular senescence and other aging mechanisms are also key factors in the development and progression of CVD. This study aims to investigate age-related susceptibility to cardiac remodeling and senescence due to PM exposure. Methods: Young and old male C57BL/6 mice were exposed to filtered or polluted air for six months using an ambient particle concentrator. Cardiac hypertrophy, fibrosis, and markers of cellular senescence (p53, p21, p-H2AX, and lipofuscin) in the myocardium were evaluated in the experimental groups. Results: PM exposure induces signs of cardiac remodeling, including cardiomyocyte enlargement and increased fibrosis, in young mice, along with elevated p53 expression. However, no significant alterations in cardiac structure or senescence markers were observed between aged mice exposed or not to PM. Conclusions: Our study indicates that younger individuals may be more vulnerable to the cardiovascular effects of chronic PM than older individuals exposed later. Further studies are needed to explore detailed mechanisms of this age-dependent response. Full article
(This article belongs to the Special Issue Research on Air Pollution and Human Exposures)
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20 pages, 8151 KiB  
Article
Numerical Simulation of Tornado-like Vortices Induced by Small-Scale Cyclostrophic Wind Perturbations
by Yuhan Liu, Yongqiang Jiang, Chaohui Chen, Yun Zhang, Hongrang He, Xiong Chen and Ruilin Zhong
Atmosphere 2025, 16(1), 108; https://doi.org/10.3390/atmos16010108 - 19 Jan 2025
Viewed by 387
Abstract
This study introduces a tornado perturbation model utilizing the cyclostrophic wind model, implemented through a shallow-water equation framework. Four numerical experiments were conducted: a single cyclonic wind perturbation (EXP1), a single low-geopotential height perturbation (EXP2), a cyclonic wind perturbation with a 0 Coriolis [...] Read more.
This study introduces a tornado perturbation model utilizing the cyclostrophic wind model, implemented through a shallow-water equation framework. Four numerical experiments were conducted: a single cyclonic wind perturbation (EXP1), a single low-geopotential height perturbation (EXP2), a cyclonic wind perturbation with a 0 Coriolis parameter (EXP3), and a single anticyclonic wind perturbation (EXP4). The outputs showed that in a static atmosphere setting, a small-scale cyclonic wind perturbation generated a tornado-like pressure structure. The centrifugal force in the central area exceeded the pressure gradient force, causing air particles to flow outward, leading to a pressure drop and strong pressure gradient. The effect of the Coriolis force is negligible for meso-γ-scale and smaller systems, while for meso-β-scale and larger systems, it begins to have a significant impact. The results indicate that a robust cyclonic and an anticyclonic wind field can potentially generate a pair of cyclonic and anticyclonic tornadoes when the horizontal vortex tubes in an atmosphere with strong vertical wind shear tilt, forming a pair of positive and negative vorticities. These tornadoes are similar but have different rotation directions. Full article
(This article belongs to the Section Meteorology)
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35 pages, 3573 KiB  
Review
Analytical Methods for Atmospheric Carbonyl Compounds: A Review
by Xiaoshuai Gao, Xin Zhang, Yan Nie, Jiemeng Bao, Junling Li, Rui Gao, Yunfeng Li, Wei Wei, Xiaoyu Yan, Yongxin Yan and Hong Li
Atmosphere 2025, 16(1), 107; https://doi.org/10.3390/atmos16010107 - 19 Jan 2025
Viewed by 481
Abstract
Atmospheric carbonyl compounds have significant impacts on the atmospheric environment and human health, making the selection of appropriate analytical techniques crucial for accurately detecting these compounds in specific environments. Based on extensive literature research, this study summarized the development history, relevant features, and [...] Read more.
Atmospheric carbonyl compounds have significant impacts on the atmospheric environment and human health, making the selection of appropriate analytical techniques crucial for accurately detecting these compounds in specific environments. Based on extensive literature research, this study summarized the development history, relevant features, and applicable scenarios of the main analytical techniques for atmospheric carbonyl compounds; pointed out the main problems and challenges in this field; and discussed the needs and prospects of future research and application. It was found that the direct sampling methods of atmospheric carbonyl compounds were applicable to low-molecular-weight carbonyl species with low reactivity, low boiling points, high polarity, and high volatility, while indirect sampling methods were suitable for a wider range and various types and phases of species. For formaldehyde, offline detection was primarily influenced by chemical reagents and reaction conditions, whereas online monitoring relied on sufficiently stable operating environments. For multiple carbonyl compounds, offline detection results were greatly influenced by detectors coupled with chromatography, whereas online monitoring techniques were applicable to all types of volatile organic compounds (VOCs), including some carbonyl compounds, providing higher temporal resolution and improved isomer identification with the development of online mass spectrometry. The combined use of proton transfer reaction-mass spectrometry (PTR-MS) and liquid chromatography-mass spectrometry (GC-MS) was suitable for the detection of carbonyl compounds in atmospheric photochemical smog chamber simulation studies. Currently, offline analytical techniques for carbonyl compounds require significant time and advanced experimental skills for multiple optimization experiments to detect a broader range of species. Online monitoring techniques face challenges such as poor stability and limited species coverage. In smog chamber simulation studies, the detection of carbonyl compounds is heavily influenced by both the sampling system and the chamber itself. Future efforts should focus on improving the environmental adaptability and automation of carbonyl compound analytical techniques, the synergistic use of various techniques, developing new sampling systems, and reducing the impact of the chamber itself on carbonyl compound detection, in order to enhance detection sensitivity, selectivity, time resolution, accuracy, and operability. Full article
(This article belongs to the Special Issue Applying Deep Learning Technology for Spatiotemporal Prediction of Air Pollution from Urban Mobile Sources)
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19 pages, 5659 KiB  
Article
Advanced Soft Computing Techniques for Monthly Streamflow Prediction in Seasonal Rivers
by Mohammed Achite, Okan Mert Katipoğlu, Veysi Kartal, Metin Sarıgöl, Muhammad Jehanzaib and Enes Gül
Atmosphere 2025, 16(1), 106; https://doi.org/10.3390/atmos16010106 - 19 Jan 2025
Viewed by 482
Abstract
The rising incidence of droughts in specific global regions in recent years, primarily attributed to global warming, has markedly increased the demand for reliable and accurate streamflow estimation. Streamflow estimation is essential for the effective management and utilization of water resources, as well [...] Read more.
The rising incidence of droughts in specific global regions in recent years, primarily attributed to global warming, has markedly increased the demand for reliable and accurate streamflow estimation. Streamflow estimation is essential for the effective management and utilization of water resources, as well as for the design of hydraulic infrastructure. Furthermore, research on streamflow estimation has gained heightened importance because water is essential not only for the survival of all living organisms but also for determining the quality of life on Earth. In this study, advanced soft computing techniques, including long short-term memory (LSTM), convolutional neural network–recurrent neural network (CNN-RNN), and group method of data handling (GMDH) algorithms, were employed to forecast monthly streamflow time series at two different stations in the Wadi Mina basin. The performance of each technique was evaluated using statistical criteria such as mean square error (MSE), mean bias error (MBE), mean absolute error (MAE), and the correlation coefficient (R). The results of this study demonstrated that the GMDH algorithm produced the most accurate forecasts at the Sidi AEK Djillali station, with metrics of MSE: 0.132, MAE: 0.185, MBE: −0.008, and R: 0.636. Similarly, the CNN-RNN algorithm achieved the best performance at the Kef Mehboula station, with metrics of MSE: 0.298, MAE: 0.335, MBE: −0.018, and R: 0.597. Full article
(This article belongs to the Special Issue The Hydrologic Cycle in a Changing Climate)
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28 pages, 20186 KiB  
Article
Long-Term Statistical Analysis of Severe Weather and Climate Events in Greece
by Vassiliki Kotroni, Antonis Bezes, Stavros Dafis, Dimitra Founda, Elisavet Galanaki, Christos Giannaros, Theodore Giannaros, Athanasios Karagiannidis, Ioannis Koletsis, George Kyros, Konstantinos Lagouvardos, Katerina Papagiannaki and Georgios Papavasileiou
Atmosphere 2025, 16(1), 105; https://doi.org/10.3390/atmos16010105 - 18 Jan 2025
Viewed by 807
Abstract
The Mediterranean faces frequent heavy precipitation, deadly heatwaves, and wildfires fueled by its climate. Greece, with its complex topography, experiences severe and extreme weather events that have escalated in recent years and are projected to continue rising under future climate conditions. This paper [...] Read more.
The Mediterranean faces frequent heavy precipitation, deadly heatwaves, and wildfires fueled by its climate. Greece, with its complex topography, experiences severe and extreme weather events that have escalated in recent years and are projected to continue rising under future climate conditions. This paper analyzes severe weather events and trends in Greece from 2010 to 2023, leveraging data from an expanded network of weather stations spanning across Greece, as well as long-term meteorological data from the reference weather station in the center of Athens. The focus includes analysis of heat waves, intense rainfall and droughts, thunderstorms, hail, tornadoes, and fire weather conditions. The societal impact of severe weather events is also discussed. The paper aims to provide both long-term (1901–2023) and recent year analyses (2010–2023). The main results show that between 2010 and 2023, Greece experienced: nearly one heatwave per summer; heavy rainfall events, most common in winter and autumn, showing a significant increase, particularly in the eastern Aegean and western continental Greece; dry spells, which are longest in southern Greece; thunderstorm and hail events peaking in spring and summer; fire weather conditions and risk peaking in southern Greece. Finally, societal impacts from weather hazards have increased in Greece over the past 14 years, with flash floods being the most frequent and damaging events, while public preparedness and effective risk communication remain low. Full article
(This article belongs to the Special Issue The Drivers and Impacts of Climate Change Over the Eastern Mediterranean)
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15 pages, 1625 KiB  
Article
Characterizing Industrial VOC Hotspots in One of Eastern China’s Largest Petrochemical Parks Using Mobile PTR–ToF–MS Measurements
by Jie Fang, Zihang Zhang, Zeye Liang, Ming Wang, Yunjiang Zhang and Xinlei Ge
Atmosphere 2025, 16(1), 104; https://doi.org/10.3390/atmos16010104 - 18 Jan 2025
Viewed by 507
Abstract
The industrial emissions of volatile organic compounds (VOCs) are a major contributor to air pollution in urban areas. Previous studies on VOC emissions in industrial zones have primarily relied on in situ monitoring techniques, which pose significant challenges in capturing high emissions peaks [...] Read more.
The industrial emissions of volatile organic compounds (VOCs) are a major contributor to air pollution in urban areas. Previous studies on VOC emissions in industrial zones have primarily relied on in situ monitoring techniques, which pose significant challenges in capturing high emissions peaks and near-source measurements on regional scales. In this study, we employed mobile proton transfer reaction–time-of-flight–mass spectrometry (PTR–ToF–MS) to identify and characterize industrial VOC hotspots in a petrochemical park in eastern China, from June to September 2021. The average total VOC concentrations in the industrial zone were 131.5 ± 227.7 ppbv, approximately 48% higher than those in the background area (88.9 ± 63.3 ppbv), reflecting the substantial emissions from industrial hotspots. Oxygenated VOCs were the most abundant components in the industrial zone (83.2 ppbv). The overall OH reactivity, aerosol formation potential, and lifetime cancer risk of the industrial zone were also substantially higher than those in the background zone. These findings emphasize the need for targeted VOC emissions controls in industrial hotspots to mitigate air quality and health risks. Full article
(This article belongs to the Special Issue Industrial Emissions: Characteristics, Impacts and Control)
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17 pages, 2396 KiB  
Article
Experimental Setup and Machine Learning-Based Prediction Model for Electro-Cyclone Filter Efficiency: Filtering of Ship Particulate Matter Emission
by Aleksandr Šabanovič, Jonas Matijošius, Dragan Marinković, Aleksandras Chlebnikovas, Donatas Gurauskis, Johannes H. Gutheil and Artūras Kilikevičius
Atmosphere 2025, 16(1), 103; https://doi.org/10.3390/atmos16010103 - 18 Jan 2025
Viewed by 498
Abstract
Ship emissions significantly impact air quality, particularly in coastal and port regions, contributing to elevated concentrations of PM2.5, and PM10, with varying effects observed across different locations. This study investigates the effectiveness of emission control policies, inland and port-specific [...] Read more.
Ship emissions significantly impact air quality, particularly in coastal and port regions, contributing to elevated concentrations of PM2.5, and PM10, with varying effects observed across different locations. This study investigates the effectiveness of emission control policies, inland and port-specific contributions to air pollution, and the health risks posed by particulate matter (PM). A regression discontinuity model at Ningbo Port revealed that ship activities show moderate PM2.5 and PM10 variations. In Busan Port, container ships accounted for the majority of emissions, with social costs from pollutants estimated at USD 31.55 million annually. Inland shipping near the Yangtze River demonstrated significant PM contributions, emphasizing regional impacts. Health risks from PM2.5, a major global toxic pollutant, were highlighted, with links to respiratory, cardiovascular, and cognitive disorders. Advances in air purification technologies, including hybrid electrostatic filtration systems, have shown promising efficiency in removing submicron particles and toxic gases, reducing energy costs. In this paper, a random forest machine learning model developed to predict particulate concentrations post-cleaning demonstrated robust performance (MAE = 0.49 P/cm3, R2 = 0.97). These findings underscore the critical need for stringent emission controls, innovative filtration systems, and comprehensive monitoring to mitigate the environmental and health impacts of ship emissions. Full article
(This article belongs to the Special Issue Shipping Emissions and Air Pollution (2nd Edition))
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21 pages, 16278 KiB  
Article
Synoptic and Mesoscale Atmospheric Patterns That Triggered the Natural Disasters in the Metropolitan Region of Belo Horizonte, Brazil, in January 2020
by Thaís Aparecida Cortez Pinto, Enrique Vieira Mattos, Michelle Simões Reboita, Diego Oliveira de Souza, Paula S. S. Oda, Fabrina Bolzan Martins, Thiago Souza Biscaro and Glauber Willian de Souza Ferreira
Atmosphere 2025, 16(1), 102; https://doi.org/10.3390/atmos16010102 - 18 Jan 2025
Viewed by 416
Abstract
Between 23 and 25 January 2020, the Metropolitan Region of Belo Horizonte (MRBH) in Brazil experienced 32 natural disasters, which affected 90,000 people, resulted in 13 fatalities, and caused economic damages of approximately USD 250 million. This study aims to describe the synoptic [...] Read more.
Between 23 and 25 January 2020, the Metropolitan Region of Belo Horizonte (MRBH) in Brazil experienced 32 natural disasters, which affected 90,000 people, resulted in 13 fatalities, and caused economic damages of approximately USD 250 million. This study aims to describe the synoptic and mesoscale conditions that triggered these natural disasters in the MRBH and the physical properties of the associated clouds and precipitation. To achieve this, we analyzed data from various sources, including natural disaster records from the National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), GOES-16 satellite imagery, soil moisture data from the Soil Moisture Active Passive (SMAP) satellite mission, ERA5 reanalysis, reflectivity from weather radar, and lightning data from the Lightning Location System. The South Atlantic Convergence Zone, coupled with a low-pressure system off the southeast coast of Brazil, was the predominant synoptic pattern responsible for creating favorable conditions for precipitation during the studied period. Clouds and precipitating cells, with cloud-top temperatures below −65 °C, over several days contributed to the high precipitation volumes and lightning activity. Prolonged rainfall, with a maximum of 240 mm day−1 and 48 mm h−1, combined with the region’s soil characteristics, enhanced water infiltration and was critical in triggering and intensifying natural disasters. These findings highlight the importance of monitoring atmospheric conditions in conjunction with soil moisture over an extended period to provide additional information for mitigating the impacts of natural disasters. Full article
(This article belongs to the Special Issue Prediction and Modeling of Extreme Weather Events)
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22 pages, 6054 KiB  
Article
Evaluation and Adjustment of Precipitable Water Vapor Products from FY-4A Using Radiosonde and GNSS Data from China
by Xiangping Chen, Yifei Yang, Wen Liu, Changzeng Tang, Congcong Ling, Liangke Huang, Shaofeng Xie and Lilong Liu
Atmosphere 2025, 16(1), 99; https://doi.org/10.3390/atmos16010099 - 17 Jan 2025
Viewed by 370
Abstract
The geostationary meteorological satellite Fengyun-4A (FY-4A) has rapidly advanced, generating abundant high spatiotemporal resolution atmospheric precipitable water vapor (PWV) products. However, remote sensing satellites are vulnerable to weather conditions, and these latest operational PWV products still require systematic validation. This study presents a [...] Read more.
The geostationary meteorological satellite Fengyun-4A (FY-4A) has rapidly advanced, generating abundant high spatiotemporal resolution atmospheric precipitable water vapor (PWV) products. However, remote sensing satellites are vulnerable to weather conditions, and these latest operational PWV products still require systematic validation. This study presents a comprehensive evaluation of FY-4A PWV products by separately using PWV data retrieved from radiosondes (RS) and the Global Navigation Satellite System (GNSS) from 2019 to 2022 in China and the surrounding regions. The overall results indicate a significant consistency between FY-4A PWV and RS PWV as well as GNSS PWV, with mean biases of 7.21 mm and −8.85 mm, and root mean square errors (RMSEs) of 7.03 mm and 3.76 mm, respectively. In terms of spatial variability, the significant differences in mean bias and RMSE were 6.50 mm and 2.60 mm between FY-4A PWV and RS PWV in the northern and southern subregions, respectively, and 5.36 mm and 1.73 mm between FY-4A PWV and GNSS PWV in the northwestern and southern subregions, respectively. The RMSE of FY-4A PWV generally increases with decreasing latitude, and the bias is predominantly negative, indicating an underestimation of water vapor. Regarding temporal differences, both the monthly and daily biases and RMSEs of FY-4A PWV are significantly higher in summer than in winter, with daily precision metrics in summer displaying pronounced peaks and irregular fluctuations. The classic seasonal, regional adjustment model effectively reduced FY-4A PWV deviations across all regions, especially in the NWC subregion with low water vapor distribution. In summary, the accuracy metrics of FY-4A PWV show distinct spatiotemporal variations compared to RS PWV and GNSS PWV, and these variations should be considered to fully realize the potential of multi-source water vapor applications. Full article
(This article belongs to the Special Issue GNSS Remote Sensing in Atmosphere and Environment (2nd Edition))
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22 pages, 4103 KiB  
Article
Seasonally Dependent Daytime and Nighttime Formation of Oxalic Acid Vapor and Particulate Oxalate in Tropical Coastal and Marine Atmospheres
by Le Yan, Yating Gao, Dihui Chen, Lei Sun, Yang Gao, Huiwang Gao and Xiaohong Yao
Atmosphere 2025, 16(1), 98; https://doi.org/10.3390/atmos16010098 - 17 Jan 2025
Viewed by 380
Abstract
Oxalic acid is the most abundant low-molecular-weight dicarboxylic acid in the atmosphere, and it plays a crucial role in the formation of new particles and cloud condensation nuclei. However, most observational studies have focused on particulate oxalate, leaving a significant knowledge gap on [...] Read more.
Oxalic acid is the most abundant low-molecular-weight dicarboxylic acid in the atmosphere, and it plays a crucial role in the formation of new particles and cloud condensation nuclei. However, most observational studies have focused on particulate oxalate, leaving a significant knowledge gap on oxalic acid vapor. This study investigated the concentrations and formation of oxalic acid vapor and oxalate in PM2.5 at a rural tropical coastal island site in south China across different seasons, based on semi-continuous measurements using an Ambient Ion Monitor-Ion Chromatograph (AIM-IC) system. We replaced the default 25 μL sampling loop on the AIM-IC with a 250 μL loop, improving the ability to distinguish the signal of oxalic acid vapor from noise. The data revealed clear seasonal patterns in the dependent daytime and nighttime formation of oxalic acid vapor, benefiting from high signal-to-noise ratios. Specifically, concentrations were 0.059 ± 0.15 μg m−3 in February and April 2023, exhibiting consistent diurnal variations similar to those of O3, likely driven by photochemical reactions. These values decreased to 0.021 ± 0.07 μg m−3 in November and December 2023, with higher nighttime concentrations likely related to dark chemistry processes, amplified by accumulation due to low mixing layer height. The concentrations of oxalate in PM2.5 were comparable to those of oxalic acid vapor, but exhibited (3–7)-day variations, superimposed on diurnal fluctuations to varying degrees. Additionally, thermodynamic equilibrium calculations were performed on the coastal data, and independent size distributions of particulate oxalate in the upwind marine atmosphere were analyzed to support the findings. Full article
(This article belongs to the Section Aerosols)
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25 pages, 11358 KiB  
Article
A New Regional Background Atmospheric Station in the Yangtze River Delta Region for Carbon Monoxide: Assessment of Spatiotemporal Characteristics and Regional Significance
by Yi Lin, Shan Li, Yan Yu, Meijing Lu, Bingjiang Chen, Yuanyuan Chen, Kunpeng Zang, Shuo Liu, Bing Qi and Shuangxi Fang
Atmosphere 2025, 16(1), 101; https://doi.org/10.3390/atmos16010101 - 17 Jan 2025
Viewed by 374
Abstract
A new meteorological station (DMS) was established at the Morning Glory summit in Zhejiang Province to provide regional background information on atmospheric composition in the Yangtze River Delta (YRD) region, China. This study investigated the first carbon monoxide (CO) records at DMS from [...] Read more.
A new meteorological station (DMS) was established at the Morning Glory summit in Zhejiang Province to provide regional background information on atmospheric composition in the Yangtze River Delta (YRD) region, China. This study investigated the first carbon monoxide (CO) records at DMS from September 2020 to January 2022. The annual average concentration of CO was 233.4 ± 3.8 ppb, which exceeded the measurements recorded at the other Asian background sites. The winter CO concentration remained elevated but peaked in March in the early spring due to the combined effect of regional emissions within the YRD and transportation impacts of North China and Southeast Asia sources. The diurnal cycle had a nocturnal peak and a morning valley but with a distinct afternoon climb, as the metropolis in the YRD contributed to a local concentration enhancement. The back trajectory analysis and the Weighted Potential Sources Contribution Function (WPSCF) maps highlighted emissions from Anhui, Jiangxi, Zhejiang, and Jiangsu provinces as significant sources. Due to well-mixed air conditions and fewer anthropogenic influences, DMS records closely aligned with the CO averages derived from the Copernicus Atmospheric Monitoring Service (CAMS) covering the YRD, confirming its representativeness for regional CO levels. This study underscored DMS as a valuable station for monitoring and understanding CO spatiotemporal characteristics in the YRD region. Full article
(This article belongs to the Section Air Quality)
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21 pages, 12342 KiB  
Article
Field Measurements of Building Air-Conditioning Heat Rejection and the Thermal Environment in Urban Areas
by Kang Mu, Qiong Suo, Fangliang Ding, Changwei Jiang, Xiaofeng Zhang and Jing Ye
Atmosphere 2025, 16(1), 100; https://doi.org/10.3390/atmos16010100 - 17 Jan 2025
Viewed by 388
Abstract
In recent years, the surge in air-conditioning ownership and usage has led to significant heat rejection, impacting the surrounding atmosphere. Despite this, studies examining the spatiotemporal effects of air-conditioning heat rejection at a block scale remain limited. Additionally, comparative studies on the role [...] Read more.
In recent years, the surge in air-conditioning ownership and usage has led to significant heat rejection, impacting the surrounding atmosphere. Despite this, studies examining the spatiotemporal effects of air-conditioning heat rejection at a block scale remain limited. Additionally, comparative studies on the role of building areas with air-conditioning systems versus natural underlying surfaces in the urban thermal environment are relatively scarce. This study employs field measurements and ArcGIS technology to investigate the local thermal and humidity environments, as well as the spatiotemporal distribution of heat rejection from air-conditioning systems in Wuyi Square, Changsha. Results show that cooling tower exhausts in commercial buildings maintain relative humidity levels of 95.2% to 99.8% during the day, enhancing surrounding humidity. At night, the humidity aligns with atmospheric levels (from 50.3% to 62.5%). The cooling tower exhaust temperature is approximately 2.2 °C lower during the day and 2.4 °C higher at night compared to the surrounding temperatures. In contrast, exhausts from split-type air-conditioning units in residential buildings have an average relative humidity about 14.2% lower than the atmosphere humidity, with temperature averages being 5.2 °C higher during the day and 6.5 °C higher at night, raising surrounding temperatures. The study also finds that natural surface areas are up to 3.1 °C cooler and 9.6% more humid compared to built environment surfaces. Furthermore, residential areas have air temperatures about 0.3 °C higher than commercial zones, with a humidity distribution approximately 0.5% lower. These findings offer a theoretical foundation for enhancing urban thermal environments and informing urban planning and design. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
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60 pages, 48151 KiB  
Article
Excitation of ULF, ELF, and VLF Resonator and Waveguide Oscillations in the Earth–Atmosphere–Ionosphere System by Lightning Current Sources Connected with Hunga Tonga Volcano Eruption
by Yuriy G. Rapoport, Volodymyr V. Grimalsky, Andrzej Krankowski, Asen Grytsai, Sergei S. Petrishchevskii, Leszek Błaszkiewicz and Chieh-Hung Chen
Atmosphere 2025, 16(1), 97; https://doi.org/10.3390/atmos16010097 - 16 Jan 2025
Viewed by 462
Abstract
The simulations presented here are based on the observational data of lightning electric currents associated with the eruption of the Hunga Tonga volcano in January 2022. The response of the lithosphere (Earth)–atmosphere–ionosphere–magnetosphere system to unprecedented lightning currents is theoretically investigated at low frequencies, [...] Read more.
The simulations presented here are based on the observational data of lightning electric currents associated with the eruption of the Hunga Tonga volcano in January 2022. The response of the lithosphere (Earth)–atmosphere–ionosphere–magnetosphere system to unprecedented lightning currents is theoretically investigated at low frequencies, including ultra low frequency (ULF), extremely low frequency (ELF), and very low frequency (VLF) ranges. The electric current source due to lightning near the location of the Hunga Tonga volcano eruption has a wide-band frequency spectrum determined in this paper based on a data-driven approach. The spectrum is monotonous in the VLF range but has many significant details at the lower frequencies (ULF, ELF). The decreasing amplitude tendency is maintained at frequencies exceeding 0.1 Hz. The density of effective lightning current in the ULF range reaches the value of the order of 10−7 A/m2. A combined dynamic/quasi-stationary method has been developed to simulate ULF penetration through the lithosphere (Earth)–atmosphere–ionosphere–magnetosphere system. This method is suitable for the ULF range down to 10−4 Hz. The electromagnetic field is determined from the dynamics in the ionosphere and from a quasi-stationary approach in the atmosphere, considering not only the electric component but also the magnetic one. An analytical/numerical method has been developed to investigate the excitation of the global Schumann resonator and the eigenmodes of the coupled Schumann and ionospheric Alfvén resonators in the ELF range and the eigenmodes of the Earth–ionosphere waveguide in the VLF range. A complex dispersion equation for the corresponding disturbances is derived. It is shown that oscillations at the first resonance frequency in the Schumann resonator can simultaneously cause noticeable excitation of the local ionospheric Alfvén resonator, whose parameters depend on the angle between the geomagnetic field and the vertical direction. VLF propagation is possible over distances of 3000–10,000 km in the waveguide Earth–ionosphere. The results of simulations are compared with the published experimental data. Full article
(This article belongs to the Special Issue Feature Papers in Upper Atmosphere (2nd Edition))
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25 pages, 4154 KiB  
Article
Assessment of Air Pollution and Lagged Meteorological Effects in an Urban Residential Area of Kenitra City, Morocco
by Mustapha Zghaid, Abdelfettah Benchrif, Mounia Tahri, Amine Arfaoui, Malika Elouardi, Mohamed Derdaki, Ali Quyou and Moulay Laarbi Ouahidi
Atmosphere 2025, 16(1), 96; https://doi.org/10.3390/atmos16010096 - 16 Jan 2025
Viewed by 514
Abstract
Complex mixtures of air pollutants, including ozone (O3), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), black carbon (BC), and fine particulate matter (PM2.5), present significant health risks. To understand the factors influencing air [...] Read more.
Complex mixtures of air pollutants, including ozone (O3), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), black carbon (BC), and fine particulate matter (PM2.5), present significant health risks. To understand the factors influencing air pollution levels and their temporal variations, comprehensive high-resolution long-term air pollution data are essential. This study analyzed the characteristics, lagged meteorological effects, and temporal patterns of six air pollutant concentrations over a one-year period at an urban residential site in Kenitra, Morocco. The results reveal pronounced seasonal and diurnal variations in pollutant levels, shaped by meteorological factors, emission sources, and local geographic conditions. PM2.5, SO2, and CO concentrations peaked during winter, while NO2 and CO exhibited consistent diurnal peaks during morning and evening rush hours across all seasons, driven by traffic emissions and nocturnal pollutant accumulation. In contrast, O3 concentrations were highest during summer afternoons due to photochemical reactions fueled by strong UV radiation, while winter levels were the lowest due to reduced sunlight. Lagged meteorological effects further highlighted the complexity of air pollutant dynamics. Meteorological factors, including temperature, wind speed, humidity, and pressure, significantly influenced pollutant levels, with both immediate and lagged effects observed. Lag analyses revealed that PM2.5 and BC levels responded to wind speed, temperature, and humidity over time, highlighting the temporal dynamics of dispersion and accumulation. CO is sensitive to temperature and pressure changes, with delayed impacts, while O3 formation was primarily influenced by temperature and wind speed, reflecting complex photochemical processes. SO2 concentrations were shaped by both immediate and lagged meteorological effects, with wind direction playing a key role in pollutant transport. These findings emphasize the importance of considering both immediate and lagged meteorological effects, as well as seasonal and diurnal variations, in developing air quality management strategies. Full article
(This article belongs to the Section Air Quality)
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9 pages, 2395 KiB  
Communication
Machine Learning-Driven Scattering Efficiency Prediction in Passive Daytime Radiative Cooling
by Changmin Shi, Jiayu Zheng, Ying Wang, Chenjie Gan, Liwen Zhang and Brian W. Sheldon
Atmosphere 2025, 16(1), 95; https://doi.org/10.3390/atmos16010095 - 16 Jan 2025
Viewed by 510
Abstract
Passive daytime radiative cooling (PDRC) has emerged as a promising, electricity-free cooling approach that reflects sunlight while radiating heat through the atmospheric transparent window. However, the design and optimization of PDRC materials remain challenging, requiring significant time and resources for experimental and numerical [...] Read more.
Passive daytime radiative cooling (PDRC) has emerged as a promising, electricity-free cooling approach that reflects sunlight while radiating heat through the atmospheric transparent window. However, the design and optimization of PDRC materials remain challenging, requiring significant time and resources for experimental and numerical modeling efforts. In this work, we developed a machine learning (ML)-driven approach to predict scattering efficiency in the wavelength of 0.3–2.5 μm, with the aim of eventually optimizing the microstructural design of PDRC materials. By employing ML models such as linear regression, neural networks, and random forests, we aimed to predict and optimize the scattering efficiency across different pore sizes and mixed-pore-size configurations. As a result, the random forest model demonstrated superior prediction performance with minimal error, effectively capturing complex, non-linear interactions between material features. We also leveraged data transformation techniques such as one-hot encoding for generative predictions in mixed-pore-size configurations. The presented ML-driven platform serves as a valuable open resource for PDRC researchers, facilitating the rapid and cost-effective optimization of PDRC materials and accelerating the development of sustainable cooling technologies. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
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18 pages, 7881 KiB  
Article
Effect of Multiple Injection Strategy Under High Ammonia Ratio on Combustion and Emissions of Liquid Ammonia/Diesel Dual DI Engine
by Zhenbin Chen, Yudong Wan, Omar I. Awad and Zhiqiang Pan
Atmosphere 2025, 16(1), 94; https://doi.org/10.3390/atmos16010094 - 16 Jan 2025
Viewed by 406
Abstract
With the increasingly prominent environmental and energy issues, emission regulations are becoming more stringent. Ammonia diesel dual fuel (ADDF) engine is one of the effective ways to reduce carbon emissions. This study investigated the effect of multiple injection strategy on the combustion and [...] Read more.
With the increasingly prominent environmental and energy issues, emission regulations are becoming more stringent. Ammonia diesel dual fuel (ADDF) engine is one of the effective ways to reduce carbon emissions. This study investigated the effect of multiple injection strategy on the combustion and emission characteristics of liquid ammonia/diesel dual direct injection (DI) engines through numerical simulation. The results showed that under the condition of maintaining the same pre injection diesel fuel and high ammonia energy ratio (80%), with the introduction of multiple injection, the peak cylinder pressure decreased and the peak phase advanced, the combustion start angle (CA10) advanced, the heat release showed a multi-stage pattern. The times of injection (TSOI) has a significant effect on combustion and emissions. As TSOI increased, ignition delay decreased, the combustion duration is shortened, and the combustion is accelerated. Notably, overall emissions of NOx and N2O have decreased, but the emissions of unburned NH3 have increased. Optimized the state of ammonia injection (SOAI) timing and ammonia injection pressure (AIP), showed that advancing SOAI timing and increasing AIP improved combustion. Advanced the SOAI timing to −8 °CA ATDC, resulted in a significant NOx emissions decrease with an increase in TSOI, reaching over 50%. Although increasing injection pressure can improve combustion, it also results in higher N2O emissions. Full article
(This article belongs to the Special Issue Renewable Strategies for Emission Reduction: A Multisectoral Approach)
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19 pages, 4884 KiB  
Article
Investigation of Vertical Profiles of Particulate Matter and Meteorological Variables up to 2.5 km in Altitude Using a Drone-Based Monitoring System
by Woo Young Kim, Sang Gu Lee, Handol Lee and Kang-Ho Ahn
Atmosphere 2025, 16(1), 93; https://doi.org/10.3390/atmos16010093 - 16 Jan 2025
Viewed by 437
Abstract
In this study, a drone-based measurement system equipped with miniaturized optical and condensation particle counters was deployed to investigate the vertical distribution of particulate matter and meteorological variables up to 2.5 km in altitude. Measurements captured at various altitudes demonstrated notable vertical variations [...] Read more.
In this study, a drone-based measurement system equipped with miniaturized optical and condensation particle counters was deployed to investigate the vertical distribution of particulate matter and meteorological variables up to 2.5 km in altitude. Measurements captured at various altitudes demonstrated notable vertical variations in particle concentration and significant correlations with meteorological factors, particularly relative humidity (RH). Near the surface, within a well-mixed boundary layer, particle concentrations remained stable despite RH changes, indicating both anthropogenic and natural influences. At higher altitudes, a clear positive relationship between RH and particle number concentration emerged, particularly for smaller particles, while temperature inversions and distinct wind patterns influenced aerosol dispersion. The unmanned aerial vehicle system’s robust performance, validated against standard meteorological tower data, underscores its potential for high-resolution atmospheric profiling. These insights are crucial for understanding particle behavior in diverse atmospheric layers and have implications for refining air quality monitoring and climate models. Future work should incorporate chemical analysis of aerosols to further expand these findings and assess their environmental impact. Full article
(This article belongs to the Special Issue Cutting-Edge Developments in Air Quality and Health)
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15 pages, 3464 KiB  
Article
Climatological Study on Cyclone Genesis and Tracks in Southern Brazil from 1979 to 2019
by Bruna Alves Oliveira Destéfani, Micael Fernando Broggio and Carlos Alberto Eiras Garcia
Atmosphere 2025, 16(1), 92; https://doi.org/10.3390/atmos16010092 - 16 Jan 2025
Viewed by 474
Abstract
This study investigates cyclone dynamics and impacts in the Southwestern Atlantic, with a focus on their effects on southern Brazil. As climate change intensifies coastal vulnerability, understanding cyclone behavior has become essential. Using the TRACK and cycloTRACK algorithms, we examined cyclone trajectories and [...] Read more.
This study investigates cyclone dynamics and impacts in the Southwestern Atlantic, with a focus on their effects on southern Brazil. As climate change intensifies coastal vulnerability, understanding cyclone behavior has become essential. Using the TRACK and cycloTRACK algorithms, we examined cyclone trajectories and cyclogenesis densities from 1979 to 2019 to analyze seasonal and spatial patterns shaped by large-scale atmospheric circulations, including the Antarctic Oscillation (AAO). The analysis explores trends in cyclone activity across various temporal and spatial scales, identifying key regions of cyclogenesis and trajectory density. Results indicate that the cycloTRACK algorithm is more effective at tracking more intense and consistent cyclones, excluding weaker systems. Seasonal patterns suggest variability in cyclone formation, likely associated with atmospheric instability and ocean–atmosphere interactions. While trends reveal an increase in cyclone passages in southern Brazil, these systems are strongly associated with extreme climatic events in the region, including coastal storms, intense precipitation, strong winds, and high waves. By clarifying cyclone dynamics and seasonal patterns, this study enhances our understanding of cyclone behavior and contributes to improved assessments of regional climate resilience in southern Brazil. Full article
(This article belongs to the Section Climatology)
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18 pages, 8177 KiB  
Technical Note
The Weather On-Demand Framework
by Ólafur Rögnvaldsson, Karolina Stanislawska and João A. Hackerott
Atmosphere 2025, 16(1), 91; https://doi.org/10.3390/atmos16010091 - 15 Jan 2025
Viewed by 909
Abstract
This paper describes the Weather On-Demand (WOD) forecasting framework which is a software stack used to run operational and on-demand weather forecasts. The WOD framework is a distributed system for the following: (1) running the Weather Research and Forecast (WRF) model for data [...] Read more.
This paper describes the Weather On-Demand (WOD) forecasting framework which is a software stack used to run operational and on-demand weather forecasts. The WOD framework is a distributed system for the following: (1) running the Weather Research and Forecast (WRF) model for data assimilation and forecasts by triggering either scheduled or on-demand jobs; (2) gathering upstream weather forecasts and observations from a wide variety of sources; (3) reducing output data file sizes for permanent storage; (4) making results available through Application Programming Interfaces (APIs); (5) making data files available to custom post-processors. Much effort is put into starting processing as soon as the required data become available, and in parallel where possible. In addition to being able to create short- to medium-range weather forecasts for any location on the globe, users are granted access to a plethora of both global and regional weather forecasts and observations, as well as seasonal outlooks from the National Oceanic and Atmospheric Administration (NOAA) in the USA through WOD integrated-APIs. All this information can be integrated with third-party software solutions via WOD APIs. The software is maintained in the Git distributed version control system and can be installed on suitable hardware, bringing the full flexibility and power of the WRF modelling system to the user in a matter of hours. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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15 pages, 4530 KiB  
Article
Analysis of COVID-19 Lockdown to Understand Air Pollution Processes and Their Impacts on Health: A Case Study in the Western Balkans
by Claudio A. Belis, Djordje Djatkov, Martina Toceva, Jasmina Knezevic, Gordana Djukanovic, Aneta Stefanovska, Nikola Golubov, Biljana Jovic and Andreas Gavros
Atmosphere 2025, 16(1), 90; https://doi.org/10.3390/atmos16010090 - 15 Jan 2025
Viewed by 443
Abstract
The effect of COVID-19 lockdown (LD) on many ambient air pollutants (NO, NO2, PM2.5, PM10, O3 and SO2) was assessed for the first time in the Western Balkans with an innovative approach that evaluates [...] Read more.
The effect of COVID-19 lockdown (LD) on many ambient air pollutants (NO, NO2, PM2.5, PM10, O3 and SO2) was assessed for the first time in the Western Balkans with an innovative approach that evaluates a variety of factors including the stringency of the LD measures, the type of location, the pollution sources, the correlation with traffic fluxes and the meteorology. To that end, observations from 10 urban sites were compared with historical time series. The time window 1 February–30 May 2020 was classified in sub-periods on the basis of the stringency of the circulation restrictions. NO2 and O3 are the pollutants most affected by restrictions to population circulation due to lockdown during the first phase of the COVID-19 pandemic, and are well correlated with traffic fluxes. A reduction in fine particulate matter (PM2.5 and PM10) concentrations is observed in all sites only during the full LD periods, while the relation between SO2 average and maximum hourly concentrations and LD periods in industrial and traffic sites vary from site to site. The reduction in NO2 concentrations during the LD resulted in a reduction in mortality associated with air pollution in the largest cities, while the interpretation of the changes in O3 and particulate matter is less clear. Full article
(This article belongs to the Section Air Quality)
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19 pages, 21003 KiB  
Article
Spatial-Temporal Pattern of Vegetation Net Primary Productivity and Its Natural Driving Factors in Ordos Section of the Yellow River Basin
by Xiaoguang Wu, Weiwei Hao, Guohua Qu and Lingyun Yang
Atmosphere 2025, 16(1), 89; https://doi.org/10.3390/atmos16010089 - 15 Jan 2025
Viewed by 392
Abstract
Weather change has a great impact on vegetation growth restoration and ecosystem service function, resulting in significant changes in vegetation net primary productivity (NPP). Therefore, based on MOD17A3 NPP data and meteorological data, this study used the slope of a one-dimensional linear regression [...] Read more.
Weather change has a great impact on vegetation growth restoration and ecosystem service function, resulting in significant changes in vegetation net primary productivity (NPP). Therefore, based on MOD17A3 NPP data and meteorological data, this study used the slope of a one-dimensional linear regression equation, Spearman correlation analysis method, and geographical detector model to reveal the spatial and temporal evolution characteristics of NPP in the Ordos section of the Yellow River Basin from 2000 to 2021 and the impact of weather change on NPP. Results: (1) NPP increased from 25.4 gC/m2 in 2000 to 60.3 gC/m2 in 2021. The NPP of vegetation in the northeastern and southern parts of the study area showed a significant increasing trend. (2) From 2000 to 2021, the evaporation showed a fluctuating downward trend, and the relative humidity, temperature, wind speed, surface temperature, and precipitation showed a fluctuating upward trend. (3) Evaporation is the most important factor hindering the growth of NPP. Precipitation, wind speed, and temperature played an important role in promoting NPP, and the average correlation coefficients were 0.62, 0.33, and 0.15, respectively. Relative humidity and surface temperature can promote NPP, but the effect is not significant. (4) The interaction results showed that the combination of temperature and precipitation, wind speed and precipitation, wind speed and temperature, precipitation and evaporation, and precipitation and relative humidity could effectively improve NPP. The interaction of climatic factors has a significant effect on the change of NPP in the Ordos section of the Yellow River Basin. The results provide a strong reference for ecological protection and restoration, the realization of dual carbon goals, and sustainable development in the Yellow River Basin. Full article
(This article belongs to the Section Climatology)
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21 pages, 5166 KiB  
Article
Meteorological Anomalies During Earthquake Preparation: A Case Study for the 1995 Kobe Earthquake (M = 7.3) Based on Statistical and Machine Learning-Based Analyses
by Masashi Hayakawa, Shinji Hirooka, Koichiro Michimoto, Stelios M. Potirakis and Yasuhide Hobara
Atmosphere 2025, 16(1), 88; https://doi.org/10.3390/atmos16010088 - 15 Jan 2025
Viewed by 424
Abstract
The purpose of this paper is to discuss the effect of earthquake (EQ) preparation on changes in meteorological parameters. The two physical quantities of temperature (T)/relative humidity (Hum) and atmospheric chemical potential (ACP) have been investigated with the use of the Japanese meteorological [...] Read more.
The purpose of this paper is to discuss the effect of earthquake (EQ) preparation on changes in meteorological parameters. The two physical quantities of temperature (T)/relative humidity (Hum) and atmospheric chemical potential (ACP) have been investigated with the use of the Japanese meteorological “open” data of AMeDAS (Automated Meteorological Data Acquisition System), which is a very dense “ground-based” network of meteorological stations with higher temporal and spatial resolutions than the satellite remote sensing open data. In order to obtain a clearer identification of any seismogenic effect, we have used the AMeDAS station data at local midnight (LT = 01 h) and our initial target EQ was chosen to be the famous 1995 Kobe EQ of 17 January 1995 (M = 7.3). Initially, we performed conventional statistical analysis with confidence bounds and it was found that the Kobe station (very close to the EQ epicenter) exhibited conspicuous anomalies in both physical parameters on 10 January 1995, just one week before the EQ, exceeding m (mean) + 3σ (standard deviation) in T/Hum and well above m + 2σ in ACP within the short-term window of one month before and two weeks after an EQ. When looking at the whole period of over one year including the day of the EQ, in the case of T/Hum only we detected three additional extreme anomalies, except in winter, but with unknown origins. On the other hand, the anomalous peak on 10 January 1995 was the largest for ACP. Further, the spatial distributions of the anomaly intensity of the two quantities have been presented using about 40 stations to provide a further support to the close relationship of this peak with the EQ. The above statistical analysis has been compared with an analysis with recent machine/deep learning methods. We have utilized a combinational use of NARX (Nonlinear Autoregressive model with eXogenous inputs) and Long Short-Term Memory (LSTM) models, which was successful in objectively re-confirming the anomalies in both parameters on the same day prior to the EQ. The combination of these analysis results elucidates that the meteorological anomalies on 10 January 1995 are considered to be a notable precursor to the EQ. Finally, we suggest a joint examination of our two meteorological quantities for their potential use in real short-term EQ prediction, as well as in the future lithosphere–atmosphere–ionosphere coupling (LAIC) studies as the information from the bottom part of LAIC. Full article
(This article belongs to the Section Meteorology)
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15 pages, 3273 KiB  
Article
Electrostatic Particle Ionization for Reduction in Livestock and Potash Dust
by Myra Martel, Matthew Taylor, Shelley Kirychuk, Kwangseok Choi, Huiqing Guo and Lifeng Zhang
Atmosphere 2025, 16(1), 87; https://doi.org/10.3390/atmos16010087 - 15 Jan 2025
Viewed by 486
Abstract
Airborne dust is an important contaminant affecting the health and the environment, and a crucial concern in many workplaces such as animal facilities and potash mines. One of the techniques used for dust control is electrostatic particle ionization (EPI). This technology has been [...] Read more.
Airborne dust is an important contaminant affecting the health and the environment, and a crucial concern in many workplaces such as animal facilities and potash mines. One of the techniques used for dust control is electrostatic particle ionization (EPI). This technology has been proven effective in reducing airborne dust; however, it has downsides, such as the generation of ozone and corrosion of electrodes. Thus, this study tested a corrosion-resistant carbon-fiber discharge electrode and compared it with electrodes commonly used in EPI systems, that is, stainless-steel and tungsten electrodes, in terms of collection efficiency for potash dust and wheat flour (representative of livestock dust), ozone production, and power consumption. The carbon-fiber electrode performed comparably to stainless-steel electrodes, particularly for potash dust, and performed better than the tungsten electrode in terms of dust collection efficiency. Moreover, it had the lowest energy consumption and generated the least amount of ozone. However, because of the limitations of this study (e.g., fewer samples, low air velocity, controlled conditions, and the use of wheat flour instead of livestock dust), tests under real barn or mining conditions are necessary to confirm the results. Full article
(This article belongs to the Special Issue Electrostatics of Atmospheric Aerosols (2nd Edition))
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23 pages, 27902 KiB  
Article
Spatio-Temporal Characteristics of Climate Extremes in Sub-Saharan Africa and Potential Impact of Oceanic Teleconnections
by Lormido Ernesto Zita, Flávio Justino, Carlos Gurjão, James Adamu and Manuel Talacuece
Atmosphere 2025, 16(1), 86; https://doi.org/10.3390/atmos16010086 - 15 Jan 2025
Viewed by 1175
Abstract
Sub-Saharan Africa (SSA) is a region vulnerable to extreme weather events due to its low level of adaptive capacity. In recent decades, SSA has been punctuated by more intense climatic phenomena that severely affect its population. Therefore, this study evaluates the performance of [...] Read more.
Sub-Saharan Africa (SSA) is a region vulnerable to extreme weather events due to its low level of adaptive capacity. In recent decades, SSA has been punctuated by more intense climatic phenomena that severely affect its population. Therefore, this study evaluates the performance of the ERA5 and CHIRPS datasets, and the spatio-temporal evolution of extreme weather indices and their potential relationship/response to climate variability modes in the Pacific, Indian, and Atlantic oceans, namely, the El Niño−Southern Oscillation, Indian Ocean Dipole, and Tropical Atlantic Variability (ENSO, IOD, and TAV). The CHIRPS dataset showed strong positive correlations with CPC in spatial patterns and similarity in simulating interannual variability and in almost all seasons. Based on daily CHIRPS and CPC data, nine extreme indices were evaluated focusing on regional trends and change detection, and the maximum lag correlation method was applied to investigate fluctuations caused by climate variability modes. The results revealed a significant decrease in total precipitation (PRCPTOT) in north−central SSA, accompanied by a reduction in Consecutive Wet Days (CWDs) and maximum 5-day precipitation indices (RX5DAYS). At the same time, there was an increase in Consecutive Dry Days (CDDs) and maximum rainfall in 1 day (RX1DAY). With regard to temperatures, absolute minimums and maximums (TNn and TXn) showed a tendency to increase in the center−north and decrease in the south of the SSA, while daily maximums and minimums (TXx and TNx) showed the opposite pattern. The IOD, TAV, and ENSO modes of climate variability influence temperature and precipitation variations in the SSA, with distinct regional responses and lags between the basins. Full article
(This article belongs to the Special Issue Air-Sea Interactions: Recent Trends, Current Progress and Future Directions)
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17 pages, 4041 KiB  
Article
Sources and Trends of CO, O3, and Aerosols at the Mount Bachelor Observatory (2004–2022)
by Noah Bernays, Jakob Johnson and Daniel Jaffe
Atmosphere 2025, 16(1), 85; https://doi.org/10.3390/atmos16010085 - 15 Jan 2025
Viewed by 467
Abstract
Understanding baseline O3 is important as it defines the fraction of O3 coming from global sources and not subject to local control. We report the occurrence and sources of high baseline ozone days, defined as a day where the daily maximum [...] Read more.
Understanding baseline O3 is important as it defines the fraction of O3 coming from global sources and not subject to local control. We report the occurrence and sources of high baseline ozone days, defined as a day where the daily maximum 8 h average (MDA8) exceeds 70 ppb, as observed at the Mount Bachelor Observatory (MBO, 2.8 km asl) in Central Oregon from 2004 to 2022. We used various indicators and enhancement ratios to categorize each high-O3 day: carbon monoxide (CO), aerosol scattering, the water vapor mixing ratio (WV), the aerosol scattering-to-CO ratio, backward trajectories, and the NOAA Hazard Mapping System Fire and Smoke maps. Using these, we identified four causes of high-O3 days at the MBO: Upper Troposphere/Lower Stratosphere intrusions (UTLS), Asian long-range transport (ALRT), a mixed UTLS/ALRT category, and events enhanced by wildfire emissions. Wildfire sources were further divided into two categories: smoke transported in the boundary layer to the MBO and smoke transported in the free troposphere from more distant fires. Over the 19-year period, 167 high-ozone days were identified, with an increasing fraction due to contributions from wildfire emissions and a decreasing fraction of ALRT events. We further evaluated trends in the O3 and CO data distributions by season. For O3, we found an overall increase in the mean and median values of 2.2 and 1.5 ppb, respectively, from the earliest part of the record (2004–2013) compared to the later part (2014–2022), but no significant linear trends in any season. For CO, we found a significant positive trend in the summer 95th percentiles, associated with increasing fires in the Western U.S., and a strong negative trend in the springtime values at all percentiles (1.6% yr−1 for 50th percentile). This decline was likely associated with decreasing emissions from East Asia. Overall, our findings are consistent with the positive trend in wildfires in the Western United States and the efforts in Asia to decrease emissions. This work demonstrates the changing influence of these two source categories on global background O3 and CO. Full article
(This article belongs to the Special Issue Measurement and Variability of Atmospheric Ozone)
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30 pages, 17518 KiB  
Article
Preserving History: Assessments and Climate Adaptations at the House of the Seven Gables in Salem, Massachusetts, USA
by Paul Wright, Susan Baker and Stephen S. Young
Atmosphere 2025, 16(1), 84; https://doi.org/10.3390/atmos16010084 - 15 Jan 2025
Viewed by 596
Abstract
Salem, Massachusetts, is one of the oldest cities in the United States (1629) and its coastal location on the Atlantic helped create one of the wealthiest cities in America during the late 18th century, but today its coastal location threatens many of its [...] Read more.
Salem, Massachusetts, is one of the oldest cities in the United States (1629) and its coastal location on the Atlantic helped create one of the wealthiest cities in America during the late 18th century, but today its coastal location threatens many of its buildings due to sea level rise and increased storm activity. The House of the Seven Gables, a National Historic Landmark District, consists of five important historic buildings, the most famous being The Turner Ingersoll Mansion (1668), more commonly known as The House of the Seven Gables. Considered one of the most important houses in America, it is also one of the most threatened historic buildings due to its location on Salem’s harbor. The House of the Seven Gables conducted a two-year study funded by Massachusetts Coastal Zone Management to evaluate the risks posed by climate change. This process included the use of data from groundwater monitoring wells and a tidal gauge installed on-site, along with soil samples and a detailed survey base plan including topography and subsurface infrastructure. The project team then used the Massachusetts Coastal Flood Risk Model (MC-FRM) to assess climate change impacts on the site in 2030, 2050, and 2070, and then created a plan for adaptations that should be implemented before those risks materialize. Strategies for adapting to storm surges, increasing groundwater, and intense surface water runoff were evaluated for their effectiveness and appropriateness for the historic site. The conclusion of the study resulted in a five-phase plan ending in the managed retreat of the historic buildings to higher ground on the existing site. This article goes beyond other research that suggests coastal retreats by demonstrating how to quantitatively evaluate current and future coastal issues with predictive models and how to set viable dates for adaptive solutions and a managed retreat. Full article
(This article belongs to the Special Issue Climate Change Challenges for Heritage Architecture)
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