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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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22 pages, 9592 KiB  
Article
Discovery of Large Methane Emissions Using a Complementary Method Based on Multispectral and Hyperspectral Data
by Xiaoli Cai, Yunfei Bao, Qiaolin Huang, Zhong Li, Zhilong Yan and Bicen Li
Atmosphere 2025, 16(5), 532; https://doi.org/10.3390/atmos16050532 - 30 Apr 2025
Viewed by 341
Abstract
As global atmospheric methane concentrations surge at an unprecedented rate, the identification of methane super-emitters with significant mitigation potential has become imperative. In this study, we utilize remote sensing satellite data with varying spatiotemporal coverage and resolutions to detect and quantify methane emissions. [...] Read more.
As global atmospheric methane concentrations surge at an unprecedented rate, the identification of methane super-emitters with significant mitigation potential has become imperative. In this study, we utilize remote sensing satellite data with varying spatiotemporal coverage and resolutions to detect and quantify methane emissions. We exploit the synergistic potential of Sentinel-2, EnMAP, and GF5-02-AHSI for methane plume detection. Employing a matched filtering algorithm based on EnMAP and AHSI, we detect and extract methane plumes within emission hotspots in China and the United States, and estimate the emission flux rates of individual methane point sources using the IME model. We present methane plumes from industries such as oil and gas (O&G) and coal mining, with emission rates ranging from 1 to 40 tons per h, as observed by EnMAP and GF5-02-AHSI. For selected methane emission hotspots in China and the United States, we conduct long-term monitoring and analysis using Sentinel-2. Our findings reveal that the synergy between Sentinel-2, EnMAP, and GF5-02-AHSI enables the precise identification of methane plumes, as well as the quantification and monitoring of their corresponding sources. This methodology is readily applicable to other satellite instruments with coarse SWIR spectral bands, such as Landsat-7 and Landsat-8. The high-frequency satellite-based detection of anomalous methane point sources can facilitate timely corrective actions, contributing to the reduction in global methane emissions. This study underscores the potential of spaceborne multispectral imaging instruments, combining fine pixel resolution with rapid revisit rates, to advance the global high-frequency monitoring of large methane point sources. Full article
(This article belongs to the Special Issue Study of Air Pollution Based on Remote Sensing (2nd Edition))
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14 pages, 2180 KiB  
Article
Validation of the Automatic Real-Time Monitoring of Airborne Pollens in China Against the Reference Hirst-Type Trap Method
by Yiwei Liu, Wen Shao, Xiaolan Lei, Wenpu Shao, Zhongshan Gao, Jin Sun, Sixu Yang, Yunfei Cai, Zhen Ding, Na Sun, Songqiang Gu, Li Peng and Zhuohui Zhao
Atmosphere 2025, 16(5), 531; https://doi.org/10.3390/atmos16050531 - 30 Apr 2025
Viewed by 269
Abstract
Background: There is a lack of automatic real-time monitoring of airborne pollens in China and no validation study has been performed. Methods: Two-year continuous automatic real-time pollen monitoring (n = 437) was completed in 2023 (3 April–31 December) and 2024 (1 April–30 November) [...] Read more.
Background: There is a lack of automatic real-time monitoring of airborne pollens in China and no validation study has been performed. Methods: Two-year continuous automatic real-time pollen monitoring (n = 437) was completed in 2023 (3 April–31 December) and 2024 (1 April–30 November) in Shanghai, China, in parallel with the standard daily pollen sampling(n = 437) using a volumetric Hirst sampler (Hirst-type trap, according to the European standard). Daily ambient particulate matter and meteorological factors were collected simultaneously. Results: Across 2023 and 2024, the daily mean pollen concentration was 7 ± 9 (mean ± standard deviation (SD)) grains/m3 by automatic monitoring and 8 ± 10 grains/m3 by the standard Hirst-type method, respectively. The spring season had higher daily pollen levels by both methods (11 ± 14 grains/m3 and 12 ± 15 grains/m3) and the daily maximum reached 106 grains/m3 and 100 grains/m3, respectively. A strong correlation was observed between the two methods by either Pearson (coefficient 0.87, p < 0.001) or Spearman’s rank correlation (coefficient 0.70, p < 0.001). Compared to the standard method, both simple (R2 = 0.76) and multiple linear regression models (R2 = 0.76) showed a relatively high goodness of fit, which remained robust using a 5-fold cross-validation approach. The multiple regression mode adjusted for five additional covariates: daily mean temperature, relative humidity, wind speed, precipitation, and PM10. In the subset of samples with daily pollen concentration ≥ 10 grains/m3 (n = 98) and in the spring season (n = 145), the simple linear models remained robust and performed even better (R2 = 0.71 and 0.83). Conclusions: This is the first validation study on automatic real-time pollen monitoring by volumetric concentrations in China against the international standard manual method. A reliable and feasible simple linear regression model was determined to be adequate, and days with higher pollen levels (≥10 grains/m3) and in the spring season showed better fitness. More validation studies are needed in places with different ecological and climate characteristics to promote the volumetric real-time monitoring of pollens in China. Full article
(This article belongs to the Section Air Quality)
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26 pages, 15535 KiB  
Article
Analytical Approach to Enhancing Efficiency of Silt Loading Collection in EPA Vacuum Sweep Method Using K-Means Clustering
by Ho-jun Yoo and In-tai Kim
Atmosphere 2025, 16(5), 530; https://doi.org/10.3390/atmos16050530 - 30 Apr 2025
Viewed by 231
Abstract
This study explores the application of K-means clustering to optimize the selection of sampling locations for suspended silt loading (sL) on asphalt pavements, addressing the limitations of traditional random sampling methods in the EPA method. The objective was to identify reliable sampling points [...] Read more.
This study explores the application of K-means clustering to optimize the selection of sampling locations for suspended silt loading (sL) on asphalt pavements, addressing the limitations of traditional random sampling methods in the EPA method. The objective was to identify reliable sampling points for road dust concentration measurement, with a focus on improving the accuracy of data collection using the vacuum sweep method. The elbow method was used to determine the optimal number of clusters, revealing that three clusters were ideal for 25 m intervals and five for 100 m intervals. The clustering analysis identified specific sampling locations within the 25 m and 100 m road sections, such as 1.5–4.5 m and 12–18 m, and 15–18 m, 39–42 m, 57 m, 69 m, and 87 m, respectively, which adequately captured sL characteristics. The silhouette score of 0.6247 confirmed the effectiveness of the clustering method in distinguishing distinct groups with similar sL characteristics. The comparison of clustered versus non-clustered sections across 15 pavement segments showed an error rate of approximately 6%. Properly selecting sampling points ensures more accurate dust concentration data, which is crucial for effective road maintenance and environmental management. The findings highlight that optimizing the sampling process can significantly enhance the precision of dust monitoring, especially in areas with varying sL characteristics. Full article
(This article belongs to the Special Issue Traffic Related Emission (3rd Edition))
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17 pages, 2511 KiB  
Article
Can GCMs Simulate ENSO Cycles, Amplitudes, and Its Teleconnection Patterns with Global Precipitation?
by Chongya Ma, Jiaqi Li, Yuanchun Zou, Jiping Liu and Guobin Fu
Atmosphere 2025, 16(5), 507; https://doi.org/10.3390/atmos16050507 - 27 Apr 2025
Viewed by 328
Abstract
The ability of a general circulation model (GCM) to capture the variability of El Niño–Southern Oscillation (ENSO) is not only a scientific issue of climate model performance, but also critical for climate change and variability impact studies. Here, we assess 48 CMIP5 GCMs [...] Read more.
The ability of a general circulation model (GCM) to capture the variability of El Niño–Southern Oscillation (ENSO) is not only a scientific issue of climate model performance, but also critical for climate change and variability impact studies. Here, we assess 48 CMIP5 GCMs for their skill in simulating ENSO interdecadal variability and its teleconnection with precipitation globally. The results show that (1) only 22 out of 48 GCMs display interdecadal variability that is similar to the observations; (2) the ensemble of the 48 GCMs captures the ENSO–precipitation teleconnection at the global scale; (3) no single GCM can capture the observed ENSO–precipitation teleconnection globally; and (4) a GCM that can realistically simulate ENSO variability does not necessarily capture the ENSO-precipitation teleconnection, and vice versa. The results could also be used by climate change impact studies to select suitable GCMs, especially for regions with a statistically significant teleconnection between ENSO and precipitation, as well as for the comparison of CMIP5 and CMIP6. Full article
(This article belongs to the Special Issue Novel Approaches to Predict Extreme Events in Atmospheric Flows: From Turbulence to Climate)
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14 pages, 5256 KiB  
Article
The Spatiotemporal Variation Trends of Major Air Pollutants in Beijing from 2014 to 2023
by Yangyang Xie and Jiaqing Zhao
Atmosphere 2025, 16(5), 494; https://doi.org/10.3390/atmos16050494 - 24 Apr 2025
Viewed by 361
Abstract
Based on the hourly concentration data of PM2.5, PM10, SO2, NO2, CO, and O3 from 35 environmental monitoring sites in Beijing between 1 January 2014 and 31 December 2023, this paper investigated the annual [...] Read more.
Based on the hourly concentration data of PM2.5, PM10, SO2, NO2, CO, and O3 from 35 environmental monitoring sites in Beijing between 1 January 2014 and 31 December 2023, this paper investigated the annual average concentration variation of these pollutants, the differences between regions, and the factors influencing these changes and differences. Seasonal variations in the pollutants are examined through monthly average concentrations, and Pearson correlation coefficients are used to study their relationships. The results are as follows: (1) Over the past decade, the concentrations of PM2.5, PM10, SO2, NO2, and CO have decreased by −67.5%, −58.6%, −81.4%, −51.9%, and −59.3%, respectively, indicating significant progress in controlling these pollutants. However, O3 fluctuates significantly between 57 μg/m3 and 66 μg/m3, suggesting the need to improve O3 management. (2) Air pollution levels exhibit distinct spatial variations, with better air quality in mountainous and suburban areas compared to more heavily trafficked urban zones, emphasizing the need for localized control strategies. (3) The correlation coefficients between PM2.5, PM10, SO2, NO2, and CO all exceeded 0.90, indicating strong positive correlations. In contrast, O3 showed negative correlations with these five pollutants, with its most pronounced negative correlation being NO2. Full article
(This article belongs to the Section Air Quality)
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19 pages, 3144 KiB  
Article
Short-Term Temporal Variability of Radon in Finnish Dwellings and the Use of Temporal Correction Factors
by Tuukka Turtiainen, Katja Kojo and Päivi Kurttio
Atmosphere 2025, 16(5), 489; https://doi.org/10.3390/atmos16050489 - 23 Apr 2025
Viewed by 363
Abstract
(1) Background: Affordable electronic radon instruments have become increasingly popular as alternatives to traditional home radon measurements, which require a minimum duration of two months. This study aimed to determine how results obtained from these devices should be interpreted and whether short-term measurements [...] Read more.
(1) Background: Affordable electronic radon instruments have become increasingly popular as alternatives to traditional home radon measurements, which require a minimum duration of two months. This study aimed to determine how results obtained from these devices should be interpreted and whether short-term measurements lasting 2–5 days can be reliably used to assess the need for radon remediation in buildings, estimate residents’ exposure, or assess public exposure. (2) Methods: A year-long radon measurement was conducted in 55 dwellings, selected to represent the Finnish housing stock as accurately as possible. Radon concentrations were recorded hourly, and the results were analysed using probabilistic analysis to calculate the likelihood of erroneous assessments. (3) Results: If a maximum false-negative rate of 1% is accepted, the action level for a 2–5-day measurement is 90–100 Bq/m3. For measurements exceeding this threshold, a longer measurement period is necessary. (4) Conclusions: Based on this study, short-term radon measurements cannot yet be recommended as a replacement for current methods. However, the study revealed significant radon level fluctuations in September, suggesting that this period should be reconsidered for inclusion in the measurement season. Full article
(This article belongs to the Special Issue Atmospheric Radon Concentration Monitoring and Measurements (2nd Edition))
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32 pages, 13922 KiB  
Article
Urban Air Pollution in the Global South: A Never-Ending Crisis?
by Rasa Zalakeviciute, Jesus Lopez-Villada, Alejandra Ochoa, Valentina Moreno, Ariana Byun, Esteban Proaño, Danilo Mejía, Santiago Bonilla-Bedoya, Yves Rybarczyk and Fidel Vallejo
Atmosphere 2025, 16(5), 487; https://doi.org/10.3390/atmos16050487 - 22 Apr 2025
Viewed by 671
Abstract
Among the challenges the human population needs to address are threats of global pandemics, increasing socioeconomic inequality, especially in developing countries, and anthropogenic climate change. The latter’s effect has been amplified with the arrival of 2023/24 El Niño, causing an exceptional drought in [...] Read more.
Among the challenges the human population needs to address are threats of global pandemics, increasing socioeconomic inequality, especially in developing countries, and anthropogenic climate change. The latter’s effect has been amplified with the arrival of 2023/24 El Niño, causing an exceptional drought in the Amazon basin, significantly affecting fire conditions and hydroelectric power production in several South American countries, including Ecuador. This study analyzes five criteria pollutants—carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and particulate matter ≤ 2.5 µm (PM2.5)—during 2019–2024 in Quito, Ecuador, a high-elevation tropical metropolis. Despite long-term efforts to regulate emissions, air pollution levels continue to rise, driven by overlapping crises, including energy shortages, political unrest, and extreme weather events. The persistent failure to improve air quality underscores the vulnerability of developing nations to climate change-induced energy instability and the urgent need for adaptive, diversified, and resilient future energy planning. Without immediate shifts in climate adaptation policies, cities like Quito will continue to experience worsening air quality, with severe implications for public health and environmental sustainability. Full article
(This article belongs to the Special Issue Air Quality in Metropolitan Areas and Megacities (Second Edition))
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9 pages, 3305 KiB  
Article
Impact of East Pacific La Niña on Caribbean Climate
by Mark R. Jury
Atmosphere 2025, 16(4), 485; https://doi.org/10.3390/atmos16040485 - 21 Apr 2025
Viewed by 346
Abstract
Statistical cluster analysis applied to monthly 1–100 m ocean temperatures reveals El Niño–Southern Oscillation (ENSO) dipole patterns with a leading mode having opposing centers of action across the dateline and tropical east Pacific. We focus on the La Niña cold phase and study [...] Read more.
Statistical cluster analysis applied to monthly 1–100 m ocean temperatures reveals El Niño–Southern Oscillation (ENSO) dipole patterns with a leading mode having opposing centers of action across the dateline and tropical east Pacific. We focus on the La Niña cold phase and study its impact on the Caribbean climate over the period of 1980–2024. East dipole time scores are used to identify composite years, and anomaly patterns are calculated for Jan-Jun and Jul-Dec. Convective responses over the Caribbean exhibit seasonal contrasts: dry winter–spring and wet summer–autumn. Trade winds and currents across the southern Caribbean weaken and lead to anomalous warming of upper ocean temperatures. Sustained coastal upwelling off Peru and Ecuador during east La Niña is teleconnected with easterly wind shear and tropical cyclogenesis over the Caribbean during summer, leading to costly impacts. This ocean–atmosphere coupling is quite different from the more common central Pacific ENSO dipole. Full article
(This article belongs to the Special Issue Recent Advances in Air-Sea Interactions, Climate Variability, and Predictability (2nd Edition))
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17 pages, 2582 KiB  
Article
Atmospheric Pollution Particulate Matter Absorption Efficiency by Bryophytes in Laboratory Conditions
by Juta Karklina, Edgars Karklins, Lilita Abele, Jean-Baptiste Renard and Liga Strazdina
Atmosphere 2025, 16(4), 479; https://doi.org/10.3390/atmos16040479 - 19 Apr 2025
Viewed by 419
Abstract
The World Health Organization (WHO) has recognized Particulate Matter (PM) as the main threat to human health from air pollution. One of the solutions is Green Infrastructure (GI), which uses different plants to mitigate pollution. Among these plants are bryophytes (or more commonly [...] Read more.
The World Health Organization (WHO) has recognized Particulate Matter (PM) as the main threat to human health from air pollution. One of the solutions is Green Infrastructure (GI), which uses different plants to mitigate pollution. Among these plants are bryophytes (or more commonly used mosses), which have easier maintenance, lighter weight, and durability compared to vascular plants. However, currently, there is limited knowledge of its effectiveness in air pollution mitigation. By addressing this gap in current scientific knowledge, more effective deployment of GI could be introduced by municipalities for society’s health benefits. This study aimed to evaluate three species of mosses (Dicranum scoparium, Plagiomnium affine, and Hypnum cupressiforme) and one thuja (Thuja plicata) as a control species for a possible GI vertical barrier for local de-pollution. The objective was to assess different moss species’ effectiveness in air pollution PM2.5 and PM10 absorption in a laboratory setting. The practical experiment was conducted from June–July 2024 in the Laboratory of the Physics and Chemistry of Environment and Space in Orleans (LPC2E-CNRS), France. For the experiment, a unique air pollution chamber was engineered and built with a linear barrier of GI inside to measure pollution absorption before and after the barrier. With the obtained data from the sensors, the efficiency of the vegetation barrier was calculated. The total average efficiency of all 18 tests and tested moss species is 41% for PM2.5 and 47% for PM10 mass concentrations. Efficiency shows moss species’ maximum or optimal ability to absorb pollution PM2.5 and PM10 in laboratory environments, with the limitations indicated in this article. This research is an essential step towards further and more profound research on the effectiveness of GI barriers of mosses in urban environments. It significantly contributes to understanding GI effects on air pollution and presents the results for specific moss species and their capacity for PM2.5 and PM10 mitigation in the air. The novelty of the study lies in a particular application of the chosen moss species. Full article
(This article belongs to the Section Air Pollution Control)
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18 pages, 5894 KiB  
Article
Correlation Analysis Between Total Electron Content and Geomagnetic Activity: Climatology of Latitudinal, Seasonal and Diurnal Dependence
by Plamen Mukhtarov and Rumiana Bojilova
Atmosphere 2025, 16(4), 478; https://doi.org/10.3390/atmos16040478 - 19 Apr 2025
Viewed by 232
Abstract
The basic concept of this study is to investigate, by correlation analysis, the relationship between geomagnetic activity and Total Electron Content (TEC) for the period from 1994 to 2023. The global TEC data used have been recalculated to a coordinate system with a [...] Read more.
The basic concept of this study is to investigate, by correlation analysis, the relationship between geomagnetic activity and Total Electron Content (TEC) for the period from 1994 to 2023. The global TEC data used have been recalculated to a coordinate system with a modip latitude and geographical longitude. In the analysis of the parameters used, the global index of geomagnetic activity, Kp, and TEC were converted into relative values, showing the deviation from stationary (quiet) conditions. The investigation defined theoretical cross-correlation functions that allow estimating the time lag constant from the shift of the maximum cross-correlation. The seasonal dependence of the ionospheric response was investigated by splitting it into three monthly segments centered on the equinox and solstice months. The dependence of the ionospheric response on local time was studied by creating time series, including those longitudes at which, at a given moment, the local time coincides with the selected one. The results show the following peculiarities in the TEC response: the type of ionospheric response (positive or negative) in each of the latitudinal zones (auroral ovals, mid-latitude and low-latitude) depends on the season, the local time of the geomagnetic storm and the specific physical mechanism of impact. Full article
(This article belongs to the Section Upper Atmosphere)
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15 pages, 1785 KiB  
Article
Typhoon-Induced High PM10 Concentration Events in South Korea: A Comprehensive Analysis of Pre-, During, and Post-Typhoon Periods
by Hana Na and Woo-Sik Jung
Atmosphere 2025, 16(4), 473; https://doi.org/10.3390/atmos16040473 - 18 Apr 2025
Viewed by 274
Abstract
This study challenges the commonly held belief that typhoons universally improve air quality by dispersing pollutants, offering new insights into their complex effects on PM10 concentrations. Through a comprehensive analysis of long-term data (2001–2021) from seven major South Korean cities, we demonstrate that [...] Read more.
This study challenges the commonly held belief that typhoons universally improve air quality by dispersing pollutants, offering new insights into their complex effects on PM10 concentrations. Through a comprehensive analysis of long-term data (2001–2021) from seven major South Korean cities, we demonstrate that typhoons can lead to significant increases in PM10 concentrations, particularly before and after their passage, under specific meteorological conditions. Contrary to the prevailing assumption, PM10 levels often rise before typhoons due to atmospheric stagnation, and after typhoons due to subsidence and long-range pollutant transport. Our results indicate that the post-typhoon period is particularly prone to high-PM10 events, with PM10 concentrations increasing by 84.5% in Incheon, 60.8% in Busan, and 62.3% in Gwangju. A case study of Typhoon MITAK revealed that pre-typhoon atmospheric conditions contributed to PM10 concentrations exceeding 81 μg/m3 in Seoul, a level classified as ‘unhealthy’ by Korean air quality standards. These findings challenge existing perceptions and provide essential insights into the complex relationship between typhoons and air pollution. The study underscores the importance of understanding the nuanced dynamics of typhoon-induced air pollution and its implications for air quality management, particularly in the context of ongoing climate change and urbanization. Moreover, the integration of real-time monitoring data into predictive air quality models could enhance the ability to mitigate the adverse effects of typhoon-induced air pollution in vulnerable regions. Full article
(This article belongs to the Section Meteorology)
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15 pages, 6167 KiB  
Article
Comparison of Sensors for Air Quality Monitoring with Reference Methods in Zagreb, Croatia
by Silvije Davila, Marija Jelena Lovrić Štefiček, Ivan Bešlić, Gordana Pehnec, Marko Marić and Ivana Hrga
Atmosphere 2025, 16(4), 472; https://doi.org/10.3390/atmos16040472 - 18 Apr 2025
Viewed by 332
Abstract
Within the scope of “Eco Map of Zagreb” project, eight sensor sets (type AQMeshPod) were set up at an automatic measuring station at the Institute for Medical Research and Occupational Health (IMROH) for comparison with reference methods for air quality measurement during 2018. [...] Read more.
Within the scope of “Eco Map of Zagreb” project, eight sensor sets (type AQMeshPod) were set up at an automatic measuring station at the Institute for Medical Research and Occupational Health (IMROH) for comparison with reference methods for air quality measurement during 2018. This station is a city background station within the Zagreb network for air quality monitoring, where measurements of SO2, CO, NO2, O3, PM10 and PM2.5, are performed using standardized methods accredited according to EN ISO/IEC 17025. This paper presents a comparison of pollutant mass concentrations determined by sensors with reference methods. The data were compared and filtered to remove outliers and handle deviations between the results obtained by sensors and reference methods, considering the different approaches to gas and PM data. A comparison of sensor results with the reference methods showed a large scattering of all gaseous pollutants while the comparison for PM10 and PM2.5 indicated a satisfactory low dispersion. The results of a regression analysis showed a significant seasonal dependence for all pollutants. Significant statistical differences between the reference methods and sensors for the whole year and in all seasons for all gas pollutants, as well as for PM10, were observed, while for PM2.5 statistical significance showed varying results. Full article
(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)
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18 pages, 7773 KiB  
Article
Expanding Lake Area on the Changtang Plateau Amidst Global Lake Water Storage Declines: An Exploration of Underlying Factors
by Da Zhi, Yang Pu, Chuan Jiang, Jiale Hu and Yujie Nie
Atmosphere 2025, 16(4), 459; https://doi.org/10.3390/atmos16040459 - 16 Apr 2025
Viewed by 306
Abstract
The remarkable expansion of lake areas across the Changtang Plateau (CTP, located in the central Tibetan Plateau) since the late 1990s has drawn considerable scientific interest, presenting a striking contrast to the global decline in natural lake water storage observed during the same [...] Read more.
The remarkable expansion of lake areas across the Changtang Plateau (CTP, located in the central Tibetan Plateau) since the late 1990s has drawn considerable scientific interest, presenting a striking contrast to the global decline in natural lake water storage observed during the same period. This study systematically investigates the mechanisms underlying lake area variations on the CTP by integrating glacierized area changes derived from the Google Earth Engine (GEE) platform with atmospheric circulation patterns from the ERA5 reanalysis dataset. Our analysis demonstrates that the limited glacier coverage on the CTP exerted significant influence only on glacial lakes in the southern region (r = −0.65, p < 0.05). The widespread lake expansion across the CTP predominantly stems from precipitation increases (r = 0.74, p < 0.01) associated with atmospheric circulation changes. Enhanced Indian summer monsoon (ISM) activity facilitates anomalous moisture transport from the Indian Ocean to the southwestern CTP, manifesting as increased specific humidity (Qa) in summer. Simultaneously, the weakened westerly jet stream reinforces moisture convergence across the CTP, driving enhanced annual precipitation. By coupling glacier coverage variations with atmospheric processes, this research establishes that precipitation anomalies rather than glacial meltwater primarily govern the extensive lake expansion on the CTP. These findings offer critical insights for guiding ecological security strategies and sustainable development initiatives on the CTP. Full article
(This article belongs to the Special Issue Advances in Methods for the Investigation of the Atmospheric Water Cycle)
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15 pages, 2513 KiB  
Article
Analysis of Flux Contribution Area in a Peatland of the Permafrost Zone in the Greater Khingan Mountains
by Jizhe Lian, Li Sun, Yongsi Wang, Xianwei Wang and Yu Du
Atmosphere 2025, 16(4), 452; https://doi.org/10.3390/atmos16040452 - 14 Apr 2025
Viewed by 306
Abstract
Flux contribution area analysis is a valuable method for identifying greenhouse gas flux sources and their spatiotemporal variations. Flux footprint models are commonly applied to determine the origin of flux observations and estimate the location, size, and relative contributions of different flux source [...] Read more.
Flux contribution area analysis is a valuable method for identifying greenhouse gas flux sources and their spatiotemporal variations. Flux footprint models are commonly applied to determine the origin of flux observations and estimate the location, size, and relative contributions of different flux source regions. Based on eddy covariance observation data, this study utilized the Kljun model and ART Footprint Tool to analyze the source area dynamics of peatland CO2 fluxes in the permafrost region of the Greater Khingan Mountains, examining the distribution characteristics of flux contribution areas across different seasons, and atmospheric conditions, while also assessing the influence of vegetation types on these areas. The results indicated that: (1) due to regional climate conditions and terrain, the predominant wind direction in all seasons was northeast-southwest, aligning with the main flux contribution direction; (2) when the flux contribution area reached 90%, the maximum source area distances under the stable and unstable atmospheric conditions were 393.3 and 185.6 m, respectively, with the range and distance of flux contribution areas being significantly larger under stable conditions; and (3) the peatland vegetation primarily consisted of trees, tall shrubs, dwarf shrubs, sedges, and mosses, among which shrub communities dominating flux contribution areas (55.6–59.1%) contribute the most to the flux contribution areas, followed by sedges (16.7–17.7%) and mosses (18.6–19.9%), while the influence of trees (0.4–0.6%) was minimal. Full article
(This article belongs to the Special Issue Research About Permafrost–Atmosphere Interactions (2nd Edition))
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18 pages, 9863 KiB  
Article
The Stratospheric Polar Vortex and Surface Effects: The Case of the North American 2018/19 Cold Winter
by Kathrin Finke, Abdel Hannachi, Toshihiko Hirooka, Yuya Matsuyama and Waheed Iqbal
Atmosphere 2025, 16(4), 445; https://doi.org/10.3390/atmos16040445 - 11 Apr 2025
Viewed by 422
Abstract
A severe cold air outbreak hit the US and parts of Canada in January 2019, leaving behind many casualties where at least 21 people died as a consequence. According to Insurance Business America, the event cost the US about 1 billion dollars. In [...] Read more.
A severe cold air outbreak hit the US and parts of Canada in January 2019, leaving behind many casualties where at least 21 people died as a consequence. According to Insurance Business America, the event cost the US about 1 billion dollars. In the Midwest, surface temperatures dipped to the lowest on record in decades, reaching −32 °C in Chicago, Illinois, and down to −48 °C wind chill temperature in Cotton and Dakota, Minnesota, giving rise to broad media attention. A zonal wavenumber 1–3 planetary wave forcing caused a sudden stratospheric warming, with a displacement followed by a split of the polar vortex at the beginning of 2019. The common downward progression of the stratospheric anomalies stalled at the tropopause and, thus, they did not reach tropospheric levels. Instead, the stratospheric trough, developing in a barotropic fashion around 70° W, turned the usually baroclinic structure of the Aleutian high quasi-barotropic. In response, upward propagating waves over the North Pacific were reflected at its lower stratospheric, eastward tilting edge toward North America. Channeled by a dipole structure of positive and negative eddy geopotential height anomalies, the waves converged at the center of the latter and thereby strengthened the circulation anomalies responsible for the severely cold surface temperatures in most of the Midwest and Northeast US. Full article
(This article belongs to the Section Meteorology)
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19 pages, 2732 KiB  
Article
Efficacy of Ventilation Air Purifiers in Improving Classroom Air Quality: A Case Study in South Korea
by Jae Jung Lee and Soontae Kim
Atmosphere 2025, 16(4), 448; https://doi.org/10.3390/atmos16040448 - 11 Apr 2025
Viewed by 640
Abstract
Indoor air quality (IAQ) in schools significantly affects health and academic performance; however, effective interventions for poor air quality remain limited, particularly in settings with restricted natural ventilation. This study evaluated the effectiveness of ventilation-type air purifiers in improving classroom IAQ in a [...] Read more.
Indoor air quality (IAQ) in schools significantly affects health and academic performance; however, effective interventions for poor air quality remain limited, particularly in settings with restricted natural ventilation. This study evaluated the effectiveness of ventilation-type air purifiers in improving classroom IAQ in a South Korean elementary school. PM10, PM2.5, and CO2 concentrations were monitored over 18 days (14–31 May 2021) in two classrooms—one equipped with a ventilation-type air purifier and the other serving as a control. In the classroom with the air purifier, daily average concentrations of PM10, PM2.5, and CO2 decreased by 23.7%, 22.8%, and 21.1%, respectively, from baseline levels. The air purifier effectively reduced pollutant infiltration during periods of severe outdoor air pollution and stabilized pollutant levels during active class hours. Its efficacy was particularly prominent under conditions of restricted natural ventilation, high indoor activity, and fluctuating outdoor pollution levels. IAQ varied significantly between weekdays and weekends; pollutant levels were higher on weekdays due to occupancy and classroom activities, whereas weekends exhibited reduced concentrations. These findings suggest that ventilation-type air purifiers provide a viable strategy for improving IAQ in schools with limited ventilation. Future research should examine their long-term performance across different seasons and architectural settings. Full article
(This article belongs to the Section Air Quality)
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12 pages, 1210 KiB  
Article
Identifying the Signature of the Solar UV Radiation Spectrum
by Andrea-Florina Codrean, Octavian Madalin Bunoiu and Marius Paulescu
Atmosphere 2025, 16(4), 427; https://doi.org/10.3390/atmos16040427 - 6 Apr 2025
Viewed by 308
Abstract
The broadband spectrum of solar radiation is commonly characterized by indices such as the average photon energy (APE) and the blue fraction (BF). This work explores the effectiveness of the two indices in a narrower spectral band, namely the ultraviolet (UV). The analysis [...] Read more.
The broadband spectrum of solar radiation is commonly characterized by indices such as the average photon energy (APE) and the blue fraction (BF). This work explores the effectiveness of the two indices in a narrower spectral band, namely the ultraviolet (UV). The analysis is carried out from two perspectives: sensitivity to the changes in the UV spectrum and the uniqueness (each index value uniquely characterizes a single UV spectrum). The evaluation is performed in relation to the changes in spectrum induced by the main atmospheric attenuators in the UV band: ozone and aerosols. Synthetic UV spectra are generated in different atmospheric conditions using the SMARTS2 spectral solar irradiance model. The closing result is a new index for the signature of the solar UV radiation spectrum. The index is conceptually just like the BF, but it captures the specificity of the UV spectrum, being defined as the fraction of the energy of solar UV radiation held by the UV-B band. Therefore, this study gives a new meaning and a new utility to the common UV-B/UV ratio. Full article
(This article belongs to the Section Upper Atmosphere)
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20 pages, 5230 KiB  
Article
A Two-Step Downscaling Model for MODIS Land Surface Temperature Based on Random Forests
by Jiaxiong Wen, Yongjian He, Lihui Yang, Peihan Wan, Zhuting Gu and Yuqi Wang
Atmosphere 2025, 16(4), 424; https://doi.org/10.3390/atmos16040424 - 5 Apr 2025
Viewed by 363
Abstract
High-spatiotemporal-resolution surface temperature data play a crucial role in monitoring urban heat island effects. Compared with Landsat 8, MODIS surface temperature products offer high temporal resolution but suffer from low spatial resolution. To address this limitation, a two-step downscaling model (TSDM) was developed [...] Read more.
High-spatiotemporal-resolution surface temperature data play a crucial role in monitoring urban heat island effects. Compared with Landsat 8, MODIS surface temperature products offer high temporal resolution but suffer from low spatial resolution. To address this limitation, a two-step downscaling model (TSDM) was developed in this study for MODIS surface temperature by leveraging random forest (RF) algorithms. The model integrates remote sensing data, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and Normalized Difference Water Index (NDWI), alongside the land cover type, digital elevation model (DEM), slope, and aspect. Additionally, a water surface temperature fitting model (RF-WST) was established to mitigate the issue of missing data over water bodies. Validation using Landsat 8 data reveals that the average out-of-bag (OOB) error for the RF-250 m model is 0.81, that for the RF-WST model is 0.73, and that for the RF-30 m model is 0.76. The root mean square error (RMSE) for all three models is below 1.3 K. The construction of the RF-WST model successfully supplements missing water body data in MODIS outputs, enhancing spatial detail. The downscaling model demonstrates strong performance in grassland areas and shows robust applicability during winter, spring, and autumn. However, due to a half-hour temporal discrepancy in the validation data during the summer, the model exhibits reduced accuracy in that season. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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22 pages, 40986 KiB  
Article
Modeling Short-Term Drought for SPEI in Mainland China Using the XGBoost Model
by Fanchao Zeng, Qing Gao, Lifeng Wu, Zhilong Rao, Zihan Wang, Xinjian Zhang, Fuqi Yao and Jinwei Sun
Atmosphere 2025, 16(4), 419; https://doi.org/10.3390/atmos16040419 - 4 Apr 2025
Viewed by 461
Abstract
Accurate drought prediction is crucial for optimizing water resource allocation, safeguarding agricultural productivity, and maintaining ecosystem stability. This study develops a methodological framework for short-term drought forecasting using SPEI time series (1979–2020) and evaluates three predictive models: (1) a baseline XGBoost model (XGBoost1), [...] Read more.
Accurate drought prediction is crucial for optimizing water resource allocation, safeguarding agricultural productivity, and maintaining ecosystem stability. This study develops a methodological framework for short-term drought forecasting using SPEI time series (1979–2020) and evaluates three predictive models: (1) a baseline XGBoost model (XGBoost1), (2) a feature-optimized XGBoost variant incorporating Pearson correlation analysis (XGBoost2), and (3) an enhanced CPSO-XGBoost model integrating hybrid particle swarm optimization with dual mechanisms of binary feature selection and parameter tuning. Key findings reveal spatiotemporal prediction patterns: temporal-scale dependencies show all models exhibit limited capability at SPEI-1 (R2: 0.32–0.41, RMSE: 0.68–0.79) but achieve progressive accuracy improvement, peaking at SPEI-12 where CPSO-XGBoost attains optimal performance (R2: 0.85–0.90, RMSE: 0.33–0.43) with 18.7–23.4% error reduction versus baselines. Regionally, humid zones (South China/Central-Southern) demonstrate peak accuracy at SPEI-12 (R2 ≈ 0.90, RMSE < 0.35), while arid regions (Northwest Desert/Qinghai-Tibet Plateau) show dramatic improvement from SPEI-1 (R2 < 0.35, RMSE > 1.0) to SPEI-12 (R2 > 0.85, RMSE reduction > 52%). Multivariate probability density analysis confirms the model’s robustness through enhanced capture of nonlinear atmospheric-land interactions and reduced parameterization uncertainties via swarm intelligence optimization. The CPSO-XGBoost’s superiority stems from synergistic optimization: binary particle swarm feature selection enhances input relevance while adaptive parameter tuning improves computational efficiency, collectively addressing climate variability challenges across diverse terrains. These findings establish an advanced computational framework for drought early warning systems, providing critical support for climate-resilient water management and agricultural risk mitigation through spatiotemporally adaptive predictions. Full article
(This article belongs to the Special Issue Advances in Methods for the Investigation of the Atmospheric Water Cycle)
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13 pages, 485 KiB  
Article
Long-Term Trends in PM10, PM2.5, and Trace Elements in Ambient Air: Environmental and Health Risks from 2020 to 2024
by Heba M. Adly and Saleh A. K. Saleh
Atmosphere 2025, 16(4), 415; https://doi.org/10.3390/atmos16040415 - 3 Apr 2025
Viewed by 650
Abstract
This study aimed to assess the long-term trends in PM10, PM2.5, and hazardous trace elements in Makkah from 2020 to 2024, evaluating seasonal variations, health risks, and potential mitigation strategies. The results indicated that the PM10 concentrations ranged [...] Read more.
This study aimed to assess the long-term trends in PM10, PM2.5, and hazardous trace elements in Makkah from 2020 to 2024, evaluating seasonal variations, health risks, and potential mitigation strategies. The results indicated that the PM10 concentrations ranged from a minimum of 127.7 ± 14.2 µg/m3 (2020) to a maximum of 138.3 ± 15.7 µg/m3 (2024), while PM2.5 levels varied between 100.7 ± 18.7 µg/m3 and 109.8 ± 21.3 µg/m3. A seasonal analysis showed the highest PM10 and PM2.5 levels during winter (147.8 ± 16.4 µg/m3 and 119.5 ± 21.7 µg/m3 in 2024, respectively), coinciding with lower wind speeds and reduced dispersion. Among the nine trace elements analyzed, Cr VI exhibited the highest increase from 0.008 ± 0.001 µg/m3 (2020) to 0.012 ± 0.001 µg/m3 (2024), while Cd and Ni also rose significantly. The excess cancer risk (ECR) associated with these pollutants exceeded the recommended threshold, with a strong correlation between PM10 and ECR (r = 0.85–0.93, p < 0.01). These findings highlight the need for enhanced air quality monitoring and sustainable urban planning. Future research should focus on identifying the dominant pollution sources and assessing the long-term health impacts to support evidence-based air quality management in Makkah. Full article
(This article belongs to the Special Issue Global and Regional Perspectives on Particulate Matter and Air Quality: Environmental and Health Impacts, Challenges, Policies, and Solutions)
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25 pages, 18044 KiB  
Article
Atmospheric Energetics of Three Contrasting West African Monsoon Seasons as Simulated by a Regional Climate Model
by Yves Ngueto, René Laprise and Oumarou Nikiéma
Atmosphere 2025, 16(4), 405; https://doi.org/10.3390/atmos16040405 - 31 Mar 2025
Viewed by 288
Abstract
The West African atmospheric energy budget is assessed for the first time across three contrasting monsoon seasons (dry, wet, and moderate) using the latest version of the Canadian Regional Climate Model (CRCM6/GEM5). The model is driven by ERA5 reanalysis from the European Centre [...] Read more.
The West African atmospheric energy budget is assessed for the first time across three contrasting monsoon seasons (dry, wet, and moderate) using the latest version of the Canadian Regional Climate Model (CRCM6/GEM5). The model is driven by ERA5 reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF). A formalism appropriate for regional climate energetics is employed to quantify the primary physical processes occurring during the West African Monsoon, with the aim of highlighting those that exhibit significant inter-seasonal variability. The atmospheric energy path shows that the time-mean available enthalpy (AM) reservoir, reflecting high surface temperatures and a lapse rate characteristic of a dry atmosphere, dominates other energy reservoirs. AM is converted into the time-mean kinetic energy (KM) and the time-variability available enthalpy (AE) reservoirs, which are converted into a time-variability kinetic energy reservoir (KE) through barotropic and baroclinic processes. AE is the lowest energy reservoir, confirming smaller temperature variations in the tropics compared to higher latitudes. Kinetic energy reservoirs KM and KE have the same order of magnitude, suggesting that mean flow is as important as eddy activities during the season. The atmospheric energy cycle computed for three contrasting rainy seasons shows that time-variability energy reservoirs (AE and KE) and main terms acting upon them, are proportional to the rainfall activity, being higher (lower) during rainy (dry) years. It also reveals that, while CA (conversion from AM to AE) and the generation term GE feed wave’s development, the frictional term DE counteracts the generation of KE to dampen the creation of transient eddies. These findings suggest that the atmospheric energetic formalism could be applied on West African seasonal forecasts and future climate simulations to implement adaptation strategies. Full article
(This article belongs to the Section Climatology)
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21 pages, 12701 KiB  
Article
An Overview of Air-Sea Heat Flux Products and CMIP6 HighResMIP Models in the Southern Ocean
by Regiane Moura, Fernanda Casagrande and Ronald Buss de Souza
Atmosphere 2025, 16(4), 402; https://doi.org/10.3390/atmos16040402 - 30 Mar 2025
Cited by 1 | Viewed by 539
Abstract
The Southern Ocean (SO) is crucial for global climate regulation by absorbing excess heat and anthropogenic CO2. However, representing air-sea heat fluxes in climate models remains a challenge, particularly in regions characterised by strong ocean–atmosphere–sea ice interactions. This study analysed air–sea [...] Read more.
The Southern Ocean (SO) is crucial for global climate regulation by absorbing excess heat and anthropogenic CO2. However, representing air-sea heat fluxes in climate models remains a challenge, particularly in regions characterised by strong ocean–atmosphere–sea ice interactions. This study analysed air–sea heat fluxes over the SO using four products and seven CMIP6 HighResMIP pairs, comparing the mean state and trends (1985–2014) of sensible and latent heat fluxes (SHF and LHF, respectively) and the impact of grid resolution refinement on their estimation. Our results revealed significant discrepancies across datasets and SO sectors, with LHF showing more consistent seasonal performance than SHF. High-resolution models better capture air–sea heat flux variability, particularly in eddy-rich regions, with climatological mean differences reaching ±20 W.m−2 and air–sea exchange variations spreading up to 30%. Most refined models exhibited enhanced spatial detail, amplifying trend magnitudes by 30–50%, with even higher values observed in some regions. Furthermore, the trend analysis showed significant regional differences, particularly in the Pacific sector, where air–sea heat fluxes showed heightened variability. Despite modelling advances, discrepancies between datasets revealed uncertainties in climate simulations, highlighting the critical need for continued improvements in climate modelling and observational strategies to accurately represent SO air–sea heat fluxes. Full article
(This article belongs to the Special Issue Recent Advances in Air-Sea Interactions, Climate Variability, and Predictability (2nd Edition))
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28 pages, 5005 KiB  
Review
Research Progress on Plasma-Assisted Catalytic Dry Reforming of Methane
by Tao Zhu, Chen Li, Xueli Zhang, Bo Yuan, Meidan Wang, Xinyue Zhang, Xudong Xu and Qian Sun
Atmosphere 2025, 16(4), 376; https://doi.org/10.3390/atmos16040376 - 26 Mar 2025
Viewed by 778
Abstract
With the significant consumption of traditional fossil fuels, emissions of greenhouse gases such as methane (CH4) and carbon dioxide (CO2) continue to rise, requiring effective treatment methods. The dry reforming of methane (DRM) offers a promising pathway for greenhouse [...] Read more.
With the significant consumption of traditional fossil fuels, emissions of greenhouse gases such as methane (CH4) and carbon dioxide (CO2) continue to rise, requiring effective treatment methods. The dry reforming of methane (DRM) offers a promising pathway for greenhouse gas mitigation by converting CH4 and CO2 into high-value syngas. However, traditional thermal catalysis is prone to catalyst deactivation due to high-temperature sintering and carbon deposition caused by side reactions. The introduction of non-thermal plasma (NTP) provides a mild reaction environment, effectively mitigating catalyst sintering and carbon deposition, extending catalyst lifespan, reducing energy consumption, and significantly enhancing reaction performance and energy efficiency. This paper reviews recent progress in plasma-assisted DRM, focusing on different plasma discharge types and catalyst materials. The synergistic effects between plasma and catalysts and the challenges and prospects of plasma-assisted DRM technology are discussed. Full article
(This article belongs to the Section Air Pollution Control)
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23 pages, 5966 KiB  
Article
Using an Artificial Neural Network to Assess Several Rainfall Estimation Algorithms Based on X-Band Polarimetric Variables in West Africa
by Fulgence Payot Akponi, Sounmaïla Moumouni, Eric-Pascal Zahiri, Modeste Kacou and Marielle Gosset
Atmosphere 2025, 16(4), 371; https://doi.org/10.3390/atmos16040371 - 25 Mar 2025
Viewed by 285
Abstract
Quantitative precipitation estimation using polarimetric radar in attenuation-prone frequency (X-band) in tropical regions characterized by convective rain systems with high intensities is a major challenge due to strong attenuations that can lead to total signal extinction over short distances. However, some authors have [...] Read more.
Quantitative precipitation estimation using polarimetric radar in attenuation-prone frequency (X-band) in tropical regions characterized by convective rain systems with high intensities is a major challenge due to strong attenuations that can lead to total signal extinction over short distances. However, some authors have addressed this issue in Benin since 2006 in the framework of the African Monsoon Multidisciplinary Analysis program. Thus, with an experimental setup consisting of an X-band polarimetric weather radar (Xport) and a network of rain gauges, investigations have started on the subject with the aim of improving rainfall estimates. Based on simulated polarimetric variables and using a Multilayer Perceptron artificial neural network, several bi-variable and tri-variable algorithms were assessed in this study. The data used in this study are of two categories: (i) simulated polarimetric variables (Rayleigh reflectivity Z, horizontal attenuation Ah, horizontal reflectivity Zh, differential reflectivity Zdr, and specific differential phase Kdp) and rainfall intensity (R) obtained from Rain Drop Size Distribution (DSD) measurements used for algorithm evaluation (training and testing); (ii) polarimetric variables measured by the Xport radar and rainfall intensity measured by rain gauges used for algorithm validation. The simulations are performed using the T-matrix code, which leverages the scattering properties of spheroidal particles. The DSD measurements taken in northwest Benin were used as input for this code. For each spectrum, the T-matrix code simulates multiple variables. The simulated data (first category) were divided into two parts: one for training and one for testing. Subsequently, the best algorithms were validated with the second category of data. The performance of the algorithms during training, testing, and validation was evaluated using metrics. The best selected algorithms are A1:R(Z,Kdp) and A12:R(Zdr,Kdp) (among the bi-variable); B2:R(Zh,Zdr,Kdp) and B3:R(Ah,Zdr,Kdp) (among the tri-variable). Tri-variable algorithms outperform bi-variable algorithms. Validation with observation data (Xport measurements and rain gauge network) showed that the algorithm B3:R(Ah,Zdr,Kdp) performs better than B2:R(Zh,Zdr,Kdp). Full article
(This article belongs to the Special Issue Applications of Meteorological Radars in the Atmosphere)
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10 pages, 4201 KiB  
Article
Reduction in Anthropogenic CO2 Emissions Detected Through Two Decades of Observation in the Tokyo Metropolitan Area
by Toshimasa Ohara, Yosuke Muto, Junichi Kurokawa, Tomohide Shimada and Mitsuo Uematsu
Atmosphere 2025, 16(4), 364; https://doi.org/10.3390/atmos16040364 - 24 Mar 2025
Viewed by 289
Abstract
Reducing CO2 emissions is a global goal aimed at mitigating climate change, but such reductions must be scientifically tracked and verified based on long-term observational data. We analyzed the long-term trend in CO2 concentration observed for a period of 19 years [...] Read more.
Reducing CO2 emissions is a global goal aimed at mitigating climate change, but such reductions must be scientifically tracked and verified based on long-term observational data. We analyzed the long-term trend in CO2 concentration observed for a period of 19 years from 2002 to 2020 at two stations in the vicinity of Tokyo, one near a mountain summit and the other suburban. The CO2 concentration was higher at the suburban station than at the mountain station, while the annual rate of increase was lower at the suburban station than at the mountain station. The difference between the CO2 concentrations at the suburban and mountain stations (ΔCO2*) showed a significant decreasing trend over the two decades. The long-term trends (−1.39 ± 0.24% yr−1) of winter-nighttime ΔCO2* closely matched the trends (−1.54 ± 0.11% yr−1) of anthropogenic CO2 emissions in the region around the two stations. Based on this similarity, we conclude that the decreasing trend in ΔCO2* corresponds to a reduction in anthropogenic CO2 emissions around the Tokyo Metropolitan Area. This is the first evidence of two-decade-scale reductions in urban CO2 emissions from long-term continuous CO2 concentration monitoring. Full article
(This article belongs to the Section Air Quality)
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23 pages, 8567 KiB  
Article
Consistency of Changes in the Ascending and Descending Positions of the Hadley Circulation Using Different Methods
by Qianye Su, Chunlei Liu, Yu Zhang, Juliao Qiu, Jiandong Li, Yufeng Xue, Ning Cao, Xiaoqing Liao, Ke Yang, Rong Zheng, Zhiting Liang, Liang Jin, Kejia Huang, Ke Jin and Nankai Zhou
Atmosphere 2025, 16(4), 367; https://doi.org/10.3390/atmos16040367 - 24 Mar 2025
Viewed by 353
Abstract
The shift in the intertropical convergence zone (ITCZ) and the poleward expansion of the Hadley circulation termini have attracted many investigations, since they affect the hydrological cycle and hence the societies and ecosystems in the tropical and subtropical areas. Using the observed precipitation [...] Read more.
The shift in the intertropical convergence zone (ITCZ) and the poleward expansion of the Hadley circulation termini have attracted many investigations, since they affect the hydrological cycle and hence the societies and ecosystems in the tropical and subtropical areas. Using the observed precipitation and three atmospheric reanalysis data sets, different methods have been employed to quantify the changes in the ITCZ position, the Hadley circulation width, terminus position, and center intensity in both hemispheres over the global and seven longitudinal sections. It is found that the ITCZ position from the centroid method is closer to the equator over the global and ocean sections than that from the maximum precipitation method and the mass streamfunction, but the variability between different methods and data sets has significant correlations. The large spread of the ITCZ latitude is mainly from the different methods used. The ITCZ position has shifted away from the equator over 1983–2023, which is consistent across data sets, and the multi-method mean trend from five significant trends is 0.22 ± 0.12°/decade over this period. The south HC branch terminus is expanding poleward; this shift, computed using different methods and data sets, is consistent, and five out of seven are significant. The terminus position shift in the north branch is mixed, and most trends are insignificant except that from P-E. The global mean south branch circulation width has a significant increasing trend, contributed mainly by the northward shift in the ITCZ position; meanwhile, the north circulation width is shrinking insignificantly over 1983–2023. The cross-equatorial atmospheric energy transport AHT and the ITCZ position θITCZ from ERA5 are generally anti-correlated, and the correlation coefficients between AHT and θITCZ from different methods are all significant. The multi-method mean northward shift of θITCZ is 3.48 °PW−1. Full article
(This article belongs to the Section Meteorology)
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19 pages, 1743 KiB  
Review
Some Recent Key Aspects of the DC Global Electric Circuit
by Michael J. Rycroft
Atmosphere 2025, 16(3), 348; https://doi.org/10.3390/atmos16030348 - 20 Mar 2025
Viewed by 930
Abstract
The DC global electric circuit, GEC, was conceived by C.T.R. Wilson more than a century ago. Powered by thunderstorms and electrified shower clouds, an electric current I ~1 kA flows up into the ionosphere, maintaining the ionospheric potential V ~250 kV with respect [...] Read more.
The DC global electric circuit, GEC, was conceived by C.T.R. Wilson more than a century ago. Powered by thunderstorms and electrified shower clouds, an electric current I ~1 kA flows up into the ionosphere, maintaining the ionospheric potential V ~250 kV with respect to the Earth’s surface. The circuit is formed by the current I, flowing through the ionosphere all around the world, down through the atmosphere remote from the current sources (J ~2 pA/m2 through a resistance R ~250 Ω), through the land and sea surface, and up to the thunderstorms as point discharge currents. This maintains a downward electric field E of magnitude ~130 V/m at the Earth’s surface away from thunderstorms and a charge Q ~−6.105 C on the Earth’s surface. The theoretical modelling of ionospheric currents and the miniscule geomagnetic field perturbations (ΔB ~0.1 nT) which they cause, as derived by Denisenko and colleagues in recent years, are reviewed. The time constant of the GEC, τ = RC, where C is the capacitance of the global circuit capacitor, is estimated via three different methods to be ~7 to 12 min. The influence of stratus clouds in determining the value of τ is shown to be significant. Sudden excitations of the GEC by volcanic lightning in Iceland in 2011 and near the Tonga eruption in 2022 enable τ to be determined, from experimental observations, as ~10 min and 8 min, respectively. It has been suggested that seismic activity, or earthquake precursors, could produce large enough electric fields in the ionosphere to cause detectable effects, either by enhanced radon emission or by enhanced thermal emission from the earthquake region; a review of the quantitative estimates of these mechanisms shows that they are unlikely to produce sufficiently large effects to be detectable. Finally, some possible links between the topics discussed and human health are considered briefly. Full article
(This article belongs to the Special Issue Atmospheric Electricity (2nd Edition))
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22 pages, 4257 KiB  
Article
Impacts of Low-Carbon Policies on Air Quality in China’s Metropolitan Areas: Evidence from a Difference-in-Differences Study
by Xuejiao Niu and Ying Liu
Atmosphere 2025, 16(3), 339; https://doi.org/10.3390/atmos16030339 - 17 Mar 2025
Viewed by 413
Abstract
Climate change and air pollution are intrinsically interconnected as carbon dioxide and air pollutants are co-emitted during fossil fuel combustion. Low-carbon policies, aimed at mitigating carbon emissions, are also anticipated to yield co-benefits for air quality; however, the extent to which regional low-carbon [...] Read more.
Climate change and air pollution are intrinsically interconnected as carbon dioxide and air pollutants are co-emitted during fossil fuel combustion. Low-carbon policies, aimed at mitigating carbon emissions, are also anticipated to yield co-benefits for air quality; however, the extent to which regional low-carbon policies can effectively achieve significant reductions in air pollutant levels remains uncertain. In China, the implementation of the low-carbon city pilot (LCCP) policy has reduced carbon emissions, but further research is needed to examine its effectiveness regarding achieving air quality co-benefits. Adopting a difference-in-differences model with a 19-year national database of air quality, this study examines whether the LCCP policy improves air quality in China’s metropolitan areas and explores how these policy initiatives address their air pollution challenges. The results indicate that, following the implementation of the LCCP policy, the mean, maximum, and standard deviation of the AQI in pilot cities decreased significantly by 9.3%, 20.8%, and 19.8%, respectively, compared to non-pilot cities. These results suggest that the LCCP policy significantly improves air quality and provide evidence that this improvement is facilitated by advancements in green technology, industrial restructuring, and the optimization of urban planning and landscape design. Full article
(This article belongs to the Special Issue Air Quality in Metropolitan Areas and Megacities (Second Edition))
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20 pages, 2997 KiB  
Article
A Case Study of Ozone Pollution in a Typical Yangtze River Delta City During Typhoon: Identifying Precursors, Assessing Health Risks, and Informing Local Governance
by Mei Wan, Xinglong Pang, Xiaoxia Yang, Kai Xu, Jianting Chen, Yinglong Zhang, Junyue Wu and Yushang Wang
Atmosphere 2025, 16(3), 330; https://doi.org/10.3390/atmos16030330 - 14 Mar 2025
Viewed by 512
Abstract
Ozone (O3) is a crucial atmospheric component that significantly affects air quality and poses considerable health risks to humans. In the coastal areas of the Yangtze River Delta, typhoons, influenced by the subtropical high-pressure system, can lead to complex ozone pollution [...] Read more.
Ozone (O3) is a crucial atmospheric component that significantly affects air quality and poses considerable health risks to humans. In the coastal areas of the Yangtze River Delta, typhoons, influenced by the subtropical high-pressure system, can lead to complex ozone pollution situations. This study aimed to explore the causes, sources, and health risks of O3 pollution during such events. Ground-based data from Jiaxing City’s key ozone precursor (VOCs) composition observations, ERA5 reanalysis data, and models CMAQ-ISAM and PMF were employed. Focusing on the severe ozone pollution event in Jiaxing from 3 to 11 September 2022, the results showed that local ozone production was the main contributor (60.8–81.4%, with an average of 72.3%), while external regional transport was secondary. Concentrations of olefins and aromatic hydrocarbons increased remarkably, playing a vital role in ozone formation. Meteorological conditions, such as reduced cloud cover during typhoon periphery transit, promoted ozone accumulation. By considering the unique respiratory exposure habits of the Chinese population, refined health risk assessments were conducted. Acrolein was found to be the main cause of chronic non-carcinogenic risks (NCRs), with NCR values reaching 1.74 and 2.02 during and after pollution. In lifetime carcinogenic risk (LCR) assessment, the mid-pollution LCR was 1.73 times higher, mainly due to 1,2-dichloroethane and benzene. This study presents a methodology that is readily adaptable to analogous pollution incidents, thereby providing a pragmatic framework to guide actionable local government policy-making aimed at safeguarding public health and mitigating urban ozone pollution. Full article
(This article belongs to the Special Issue Advances in Source Tracing and the Control of Ozone and Its Precursors)
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21 pages, 2607 KiB  
Article
Cross-Examination of Reanalysis Datasets on Elevation-Dependent Climate Change in the Third Pole Region
by Arathi Rameshan, Prashant Singh and Bodo Ahrens
Atmosphere 2025, 16(3), 327; https://doi.org/10.3390/atmos16030327 - 13 Mar 2025
Viewed by 610
Abstract
The scarcity of in situ observation stations and the unreliability of long-term satellite data necessitate the use of reanalysis datasets to study elevation-dependent climate change (EDCC) in the third pole (TP) region. We analyzed elevation-dependent temperature and precipitation patterns over TP using the [...] Read more.
The scarcity of in situ observation stations and the unreliability of long-term satellite data necessitate the use of reanalysis datasets to study elevation-dependent climate change (EDCC) in the third pole (TP) region. We analyzed elevation-dependent temperature and precipitation patterns over TP using the ECMWF Atmospheric Reanalysis Fifth Generation (ERA5), a global reanalysis product with coarse resolution, along with three high-resolution regional reanalysis datasets that cover our study domain: Indian Monsoon Data Assimilation and Analysis (IMDAA), High Asia Refined Analysis—Version 2 (HAR-v2), and Tibetan Plateau Regional Reanalysis (TPRR). Comparing the performance of the four reanalysis datasets in capturing EDCC over TP is crucial, as these datasets provide spatially and temporally consistent data at an optimum resolution that greatly aids EDCC research. Our study results reveal the following: (1) A positive elevation-dependent warming trend is observed across all four datasets in winter and autumn, with varying magnitudes of warming across the datasets. (2) All four datasets exhibit positive elevation-dependent wetting trends in all seasons, except autumn. These are primarily driven by pronounced drying trends at lower elevations and relatively minimal changes in precipitation trends at higher elevations. (3) ERA5 and IMDAA exhibit similar results in capturing elevation-dependent climate change, whereas the TPRR dataset reveals more extreme and unique features in temperature trends compared to the other three datasets. HAR-v2 shows smaller variations in temperature and precipitation trends across different elevations and seasons, in contrast to the other three datasets. While all reanalysis datasets indicate EDCC in the TP, their varying degrees of seasonal and spatial differences underscore the need for a careful evaluation before using them as reference data. Comparison of reanalysis datasets with available observational records, such as in situ measurements and satellite data, over overlapping spatial and temporal domains is essential to assess their quality. This evaluation can help identify the most suitable reanalysis dataset, or combination of datasets, to serve as reliable a reference even in regions or periods without observational data. Full article
(This article belongs to the Section Climatology)
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19 pages, 2442 KiB  
Article
Assessing the Impact of Climatic Factors and Air Pollutants on Cardiovascular Mortality in the Eastern Mediterranean Using Machine Learning Models
by Kyriaki Psistaki, Damhan Richardson, Souzana Achilleos, Mark Roantree and Anastasia K. Paschalidou
Atmosphere 2025, 16(3), 325; https://doi.org/10.3390/atmos16030325 - 12 Mar 2025
Cited by 1 | Viewed by 1395
Abstract
Cardiovascular diseases are the most common cause of death worldwide, with atmospheric pollution, and primarily particulate matter, standing out as the most hazardous environmental factor. To explore the exposure–response curves, traditional epidemiological studies rely on generalised additive or linear models and numerous works [...] Read more.
Cardiovascular diseases are the most common cause of death worldwide, with atmospheric pollution, and primarily particulate matter, standing out as the most hazardous environmental factor. To explore the exposure–response curves, traditional epidemiological studies rely on generalised additive or linear models and numerous works have demonstrated the relative risk and the attributable fraction of mortality/morbidity associated with exposure to increased levels of particulate matter. An alternative, probably more effective, procedure to address the above issue is using machine learning models, which are flexible and often outperform traditional methods due to their ability to handle both structured and unstructured data, as well as having the capacity to capture non-linear, complex associations and interactions between multiple variables. This study uses five advanced machine learning techniques to examine the contribution of several climatic factors and air pollutants to cardiovascular mortality in the Eastern Mediterranean region, focusing on Thessaloniki, Greece, and Limassol, Cyprus, covering the periods 1999–2016 and 2005–2019, respectively. Our findings highlight that temperature fluctuations and major air pollutants significantly affect cardiovascular mortality and confirm the higher health impact of temperature and finer particles. The lag analysis performed suggests a delayed effect of temperature and air pollution, showing a temporal delay in health effects following exposure to air pollution and climatic fluctuations, while the seasonal analysis suggests that environmental factors may explain greater variability in cardiovascular mortality during the warm season. Overall, it was concluded that both air quality improvements and adaptive measures to temperature extremes are critical for mitigating cardiovascular risks in the Eastern Mediterranean. Full article
(This article belongs to the Special Issue The Drivers and Impacts of Climate Change Over the Eastern Mediterranean)
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17 pages, 7826 KiB  
Article
Evaluating the Spatial Coverage of Air Quality Monitoring Stations Using Computational Fluid Dynamics
by Giannis Ioannidis, Paul Tremper, Chaofan Li, Till Riedel, Nikolaos Rapkos, Christos Boikos and Leonidas Ntziachristos
Atmosphere 2025, 16(3), 326; https://doi.org/10.3390/atmos16030326 - 12 Mar 2025
Viewed by 702
Abstract
Densely populated urban areas often experience poor air quality due to high levels of anthropogenic emissions. The population is frequently exposed to harmful gaseous and particulate pollutants, which are directly linked to various health issues, including respiratory diseases. Accurately assessing and predicting pollutant [...] Read more.
Densely populated urban areas often experience poor air quality due to high levels of anthropogenic emissions. The population is frequently exposed to harmful gaseous and particulate pollutants, which are directly linked to various health issues, including respiratory diseases. Accurately assessing and predicting pollutant concentrations within urban areas is therefore crucial. This study developed a computational fluid dynamic (CFD) model designed to capture turbulence effects that influence pollutant dispersion in urban environments. The focus was on key pollutants commonly associated with vehicular emissions, such as carbon monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOCs), and particulate matter (PM). The model was applied to the city of Augsburg, Germany, to simulate pollutant behavior at a microscale level. The primary objectives were twofold: first, to accurately predict local pollutant concentrations and validate these predictions against measurement data; second, to evaluate the representativeness of air quality monitoring stations in reflecting the broader pollutant distribution in their vicinity. The approach presented here has demonstrated that when focusing on an area within a specific radius of an air quality station, the representativeness ranges between 10% and 16%. On the other hand, when assessing the representativeness across the street of deployment, the spatial coverage of the sensor ranges between 23% and 80%. This analysis highlights that air quality stations primarily capture pollution levels from high-activity areas directly across their deployment site, rather than reflecting conditions in nearby lower-activity zones. This approach ensures a more comprehensive understanding of urban air pollution dynamics and assesses the reliability of air quality (AQ) monitoring stations. Full article
(This article belongs to the Special Issue Emerging Technologies for Observation of Air Pollution (2nd Edition))
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19 pages, 6933 KiB  
Article
Role of Position of Pacific Subtropical High in Deciding Path of Tropical Storms
by Ravi Shankar Pandey
Atmosphere 2025, 16(3), 322; https://doi.org/10.3390/atmos16030322 - 11 Mar 2025
Viewed by 507
Abstract
The Pacific Subtropical High (PSH) predominantly develops during the boreal summer (June–August) over the Northwest Pacific (NWP) basin, with August accounting for the highest tropical storm (TS) frequency (46.9%). This study examines the critical influence of the PSH’s position on TS trajectories and [...] Read more.
The Pacific Subtropical High (PSH) predominantly develops during the boreal summer (June–August) over the Northwest Pacific (NWP) basin, with August accounting for the highest tropical storm (TS) frequency (46.9%). This study examines the critical influence of the PSH’s position on TS trajectories and the consequent exposure of affected countries, utilizing four decades (1977–2016) of August TS data from the NWP. A total of 55 TSs, unaffected by other environmental factors, were analyzed. The PSH’s observed position during each TS’s turning point was delineated using a geopotential height of 500 hPa, while track sinuosity was quantified using a validated sinuosity index (SI). Three distinct TS paths were identified: an eastward PSH position leads to highly sinuous tracks, directing TSs toward Japan; a westward PSH position results in straighter tracks, steering TSs toward the South China Sea (SCS) below Taiwan; and a mid-position guides TSs toward Taiwan. These findings underscore the PSH’s pivotal role in modulating TS behavior and provide valuable insights for disaster risk management agencies to mitigate TS impacts in the NWP basin, the world’s most active TS region, responsible for one-third of global tropical cyclones. Full article
(This article belongs to the Section Meteorology)
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21 pages, 4768 KiB  
Article
Evaluation of the Spatio-Temporal Variation of Extreme Cold Events in Southeastern Europe Using an Intensity–Duration Model and Excess Cold Factor Severity Index
by Krastina Malcheva, Neyko Neykov, Lilia Bocheva, Anastasiya Stoycheva and Nadya Neykova
Atmosphere 2025, 16(3), 313; https://doi.org/10.3390/atmos16030313 - 9 Mar 2025
Viewed by 918
Abstract
Recent studies have revealed a rise in extreme heat events worldwide, while extreme cold has reduced. It is highly likely that human-induced climate forcing will double the risk of exceptionally severe heat waves by the end of the century. Although extreme heat is [...] Read more.
Recent studies have revealed a rise in extreme heat events worldwide, while extreme cold has reduced. It is highly likely that human-induced climate forcing will double the risk of exceptionally severe heat waves by the end of the century. Although extreme heat is expected to have more significant socioeconomic impacts than cold extremes, the latter contributes to a wide range of adverse effects on the environment, various economic sectors and human health. The present research aims to evaluate the contemporary spatio-temporal variations of extreme cold events in Southeastern Europe through the intensity–duration cold spell model developed for quantitative assessment of cold weather in Bulgaria. We defined and analyzed the suitability of three indicators, based on minimum temperature thresholds, for evaluating the severity of extreme cold in the period 1961–2020 across the Köppen–Geiger climate zones, using daily temperature data from 70 selected meteorological stations. All indicators show a statistically significant decreasing trend for the Cfb and Dfb climate zones. The proposed intensity–duration model demonstrated good spatio-temporal conformity with the Excess Cold Factor (ECF) severity index in classifying and estimating the severity of extreme cold events on a yearly basis. Full article
(This article belongs to the Special Issue Weather and Climate Extremes: Observations, Modeling, and Impacts (2nd Edition))
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16 pages, 4285 KiB  
Article
Jazan Rainfall’s Seasonal Shift in Saudi Arabia: Evidence of a Changing Regional Climate
by M. Nazrul Islam, Arjan O. Zamreeq, Muhammad Ismail, Turki M. A. Habeebullah and Ayman S. Ghulam
Atmosphere 2025, 16(3), 300; https://doi.org/10.3390/atmos16030300 - 4 Mar 2025
Viewed by 1131
Abstract
In recent years, rainfall in the Jazan region of southwest Saudi Arabia has significantly increased, setting new records for monthly and daily rainfall in 2024 and leading to natural disasters. The distribution of monthly rainfall in Jazan and its variations over recent decades [...] Read more.
In recent years, rainfall in the Jazan region of southwest Saudi Arabia has significantly increased, setting new records for monthly and daily rainfall in 2024 and leading to natural disasters. The distribution of monthly rainfall in Jazan and its variations over recent decades have not been analyzed yet. This study examines the changes in seasonal rainfall patterns in the Jazan region utilizing observational and reanalysis datasets from 1978 to 2024. The rescaled adjusted partial sums technique is used to detect breaks in the rainfall time series, while statistical methods are applied to analyze rainfall extremes and their trends. The average annual rainfall for the period 1978–2024 is 149.4 mm, which has increased from 131.9 mm during the earlier decades (1978–2000) to 166.2 mm in recent decades (2001–2024), reflecting an increase of 34.3 mm. The annual rainfall has been increasing significantly at a rate of 92.9 mm/decade in recent decades, compared to 74.3 mm/decade in the previous decades. There has been a marked shift in the peak rainfall season from autumn to summer, in particular moving from October to August in recent decades. The highest monthly rainfall recorded in August, reached 54.9 mm in recent decades, compared to just 15.4 mm in earlier decades. In contrast, the peak rainfall in October was 19.9 mm in previous decades, which decreased to 18.7 mm in recent decades. Notably, August 2024 marked a record-breaking rainfall of 414.8 mm, surpassing the previous high of 157.5 mm set in October 1997. These data show clear evidence of the changing climate in the region. Moreover, the number of heavy rainfall days has risen, with a total of 608 wet days documented throughout the entire period, alongside a significant increase in light, heavy, and extremely heavy rainfall days in recent decades compared to earlier ones. Hence, the region has seen a rise in heavy to extremely heavy rainfall days, including a daily record of 113.7 mm on 23 August 2024, compared to 90.0 mm on 22 October 1997. Additionally, there has been a rise in the maximum consecutive 5-day rainfall compared to the maximum 1-day rainfall. Overall, these findings show substantial changes in rainfall patterns in the Jazan region, suggesting notable climatic shifts that warrant further investigation using the automatic weather stations, radar and satellite data, as well as climate model simulations. Full article
(This article belongs to the Section Climatology)
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19 pages, 8506 KiB  
Article
Rapid Intensification of Typhoon Rammasun (2014) with Strong Vertical Wind Shear
by Weiyu Lu and X. San Liang
Atmosphere 2025, 16(3), 297; https://doi.org/10.3390/atmos16030297 - 2 Mar 2025
Viewed by 597
Abstract
From a traditional point of view, the growth of a tropical cyclone (TC) requires that the vertical wind shear (VWS) should be weak. However, Typhoon Rammasun (2014) underwent a rapid intensification (RI) even in the presence of a strong VWS background. This study [...] Read more.
From a traditional point of view, the growth of a tropical cyclone (TC) requires that the vertical wind shear (VWS) should be weak. However, Typhoon Rammasun (2014) underwent a rapid intensification (RI) even in the presence of a strong VWS background. This study investigates the counterintuive phenomenon, using the multiscale window transform (MWT) and the theory of canonical transfer. For the first time, the diagnostic results show that the strong VWS provided additional available potential energy (APE) to the mid-to-upper troposphere through baroclinic instability. This APE was converted into kinetic energy (KE) via buoyancy conversion and transported to the lower troposphere by pressure gradient, increasing the lower-troposphere wind speed. The strong VWS facilitated the RI in two main ways. First, it was via baroclinic instability. Strong VWS facilitated the transfer of APE from the background flow window to the typhoon scale window, supplying additional APE to the mid-to-upper troposphere, hence enhancing the warm-core structure. Second, the VWS direction shifted from an east-west orientation to a north-south orientation. This directional change put the typhoon’s vertical alignment from a westward tilt back to a straighter one. This effectively suppressed the destructive effects of the asymmetric circulation, and promoted the conversion of APE into KE via buoyancy conversion, hence contributed to the RI. Full article
(This article belongs to the Section Meteorology)
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15 pages, 15327 KiB  
Technical Note
Establishment and Operation of an Early Warning Service for Agrometeorological Disasters Customized for Farmers and Extension Workers at Metropolitan-Scale
by Yong-Soon Shin, Hee-Ae Lee, Sang-Hyun Park, Yong-Kyu Han, Kyo-Moon Shim and Se-Jin Han
Atmosphere 2025, 16(3), 291; https://doi.org/10.3390/atmos16030291 - 28 Feb 2025
Viewed by 528
Abstract
A farm-specific early warning system has been developed to mitigate agricultural damage caused by climate change. This system utilizes weather data at the farm level to predict crop growth, forecast weather disaster risks, and provide risk alerts to farmers and local governments. For [...] Read more.
A farm-specific early warning system has been developed to mitigate agricultural damage caused by climate change. This system utilizes weather data at the farm level to predict crop growth, forecast weather disaster risks, and provide risk alerts to farmers and local governments. For effective implementation, local governments must lead operating early warning services that reflect regional agricultural characteristics and farmers’ needs, while the central government provides foundational data. The system connects data from each region to the cloud, enabling the establishment of a nationwide integrated service operation framework that includes the central government, metropolitan cities, municipalities, and farmers. Full article
(This article belongs to the Special Issue ICT-Based High-Resolution Weather and Climate Research for an Early-Warning System for Agricultural Disasters)
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15 pages, 5421 KiB  
Article
Indoor Radon Monitoring in Residential Areas in the Vicinity of Coal Mining Operations in the Mpumalanga Province, South Africa
by Paballo M. Moshupya, Seeke C. Mohuba, Tamiru A. Abiye, Ian Korir and Sifiso Nhleko
Atmosphere 2025, 16(3), 290; https://doi.org/10.3390/atmos16030290 - 28 Feb 2025
Cited by 1 | Viewed by 699
Abstract
Coal mining and combustion have the potential to increase exposure to radon, a form of radioactive gas recognized as one of the major contributors to lung cancer incidents. In South Africa, coal is used as the primary energy source for producing electricity and [...] Read more.
Coal mining and combustion have the potential to increase exposure to radon, a form of radioactive gas recognized as one of the major contributors to lung cancer incidents. In South Africa, coal is used as the primary energy source for producing electricity and for heating, predominantly in informal settlements and township communities. Most of the existing coal-fired power plants are found in the Mpumalanga province. This paper presents long-term radon (222Rn) measurements in dwellings surrounding coal mining centres in the Mpumalanga province and evaluates their contributions to indoor radon exposures. The indoor radon measurements were conducted using solid-state nuclear track detectors and were performed during warm and cold seasons. It was found that the overall indoor radon activity concentrations ranged between 21 Bq/m3 and 145 Bq/m3, with a mean value of 40 Bq/m3. In all the measured dwellings, the levels were below the WHO reference level of 100 Bq/m3 and 300 Bq/m3 reference level recommended by the IAEA and ICRP, with the exception of one dwelling that was poorly ventilated. The results reveal that individuals residing in the surveyed homes are not exposed to radon levels higher than the WHO, ICRP, and IAEA reference levels. The main source influencing indoor radon activity concentrations was found to be primarily the concentration of uranium found in the geological formations in the area, with ventilation being an additional contributing factor of radon levels in dwellings. To maintain good air quality in homes, it is recommended that household occupants should keep their dwellings well ventilated to keep indoor radon levels as low as possible. Full article
(This article belongs to the Special Issue Atmospheric Radon Concentration Monitoring and Measurements (2nd Edition))
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17 pages, 3397 KiB  
Article
A Wind Power Density Forecasting Model Based on RF-DBO-VMD Feature Selection and BiGRU Optimized by the Attention Mechanism
by Bixiong Luo, Peng Zuo, Lijun Zhu and Wei Hua
Atmosphere 2025, 16(3), 266; https://doi.org/10.3390/atmos16030266 - 25 Feb 2025
Cited by 1 | Viewed by 333
Abstract
Wind power, as a pivotal renewable energy source, is anticipated to play a critical role in ensuring the reliability, security, and stability of the global energy supply system. Accurate prediction of wind power density (WPD) holds significant practical importance for wind farms, grid [...] Read more.
Wind power, as a pivotal renewable energy source, is anticipated to play a critical role in ensuring the reliability, security, and stability of the global energy supply system. Accurate prediction of wind power density (WPD) holds significant practical importance for wind farms, grid operators, and the entire wind power industry, as it facilitates informed decision-making, optimized resource allocation, and enhanced system performance. This paper proposes a novel WPD forecasting model based on RF-DBO-VMD feature selection and BiGRU optimized by an attention mechanism. The proposed model consists of three main stages. First, critical physical features relevant to WPD are identified using random forest (RF), effectively eliminating data redundancy and enhancing prediction efficiency. Second, the variational mode decomposition (VMD) parameters are optimized via the dung beetle optimizer (DBO) algorithm to extract independent intrinsic mode functions (IMFs), which, alongside the original data, serve as temporal feature inputs. Finally, an attention mechanism is employed to identify important information from the outputs of the BiGRU model, and the Grid Search (GS) method is used to optimize the BiGRU-Attention model, yielding optimal predictions. The experimental results demonstrate the model’s high predictive accuracy, evidenced by an R2 value of 0.9754. Notably, the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Squared Error (MSE) are substantially minimized compared to alternative models. These results highlight the model’s potential to provide effective forecasting insights for future applications, such as energy trading and power system management, which will be further explored in real-world scenarios. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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17 pages, 2790 KiB  
Article
Development of Visualization Tools for Sharing Climate Cooling Strategies with Impacted Urban Communities
by Linda Powers Tomasso, Kachina Studer, David Bloniarz, Dillon Escandon and John D. Spengler
Atmosphere 2025, 16(3), 258; https://doi.org/10.3390/atmos16030258 - 24 Feb 2025
Viewed by 591
Abstract
Intensifying heat from warming climates regularly concentrates in urban areas lacking green infrastructure in the form of green space, vegetation, and ample tree canopy cover. Nature-based interventions in older U.S. city cores can help minimize the urban heat island effect, yet neighborhoods targeted [...] Read more.
Intensifying heat from warming climates regularly concentrates in urban areas lacking green infrastructure in the form of green space, vegetation, and ample tree canopy cover. Nature-based interventions in older U.S. city cores can help minimize the urban heat island effect, yet neighborhoods targeted for cooling interventions may remain outside the decisional processes through which change affects their communities. This translational research seeks to address health disparities originating from the absence of neighborhood-level vegetation in core urban areas, with a focus on tree canopy cover to mitigate human susceptibility to extreme heat exposure. The development of LiDAR-based imagery enables communities to visualize the proposed greening over time and across seasons of actual neighborhood streets, thus becoming an effective communications tool in community-engaged research. These tools serve as an example of how visualization strategies can initiate unbiased discussion of proposed interventions, serve as an educational vehicle around the health impacts of climate change, and invite distributional and participatory equity for residents of low-income, nature-poor neighborhoods. Full article
(This article belongs to the Special Issue Advanced Studies on Climate Change in Urban Areas: Emerging Technologies and Strategies to Address Heat Waves and Improve Thermo-Hygrometric Comfort)
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24 pages, 11231 KiB  
Article
Assessing AgERA5 and MERRA-2 Global Climate Datasets for Small-Scale Agricultural Applications
by Konstantinos Soulis, Evangelos Dosiadis, Evangelos Nikitakis, Ioannis Charalambopoulos, Orestis Kairis, Aikaterini Katsogiannou, Stergia Palli Gravani and Dionissios Kalivas
Atmosphere 2025, 16(3), 263; https://doi.org/10.3390/atmos16030263 - 24 Feb 2025
Viewed by 1680
Abstract
AgERA5 (ECMWF) is a relatively new climate dataset specifically designed for agricultural applications. MERRA-2 (NASA) is also used in agricultural applications; however, it was not specifically designed for this purpose. Despite the proven value of these datasets in assessing global climate patterns, their [...] Read more.
AgERA5 (ECMWF) is a relatively new climate dataset specifically designed for agricultural applications. MERRA-2 (NASA) is also used in agricultural applications; however, it was not specifically designed for this purpose. Despite the proven value of these datasets in assessing global climate patterns, their effectiveness in small-scale agricultural contexts remains unclear. This research aims to fill this gap by assessing the suitability and performance of AgERA5 and MERRA-2 in precision irrigation management, which is crucial for regions with limited ground data availability. The wine-making region of Nemea, Greece, with its complex and challenging terrain is used as a characteristic case study. The datasets are assessed for key weather variables and for irrigation planning, using detailed local meteorological station data as a reference. The results reveal that both products have serious limitations in small scale irrigation scheduling applications in contrast to what was reported in previous studies for other regions. The uneven performance of global datasets in different regions due to lack of sufficient observation data for reanalysis data calibration was also indicated. Comparing the two datasets, AgERA5 outperforms MERRA-2, especially in precipitation and reference evapotranspiration. MERRA-2 shows comparable potential in irrigation planning, as it occasionally matches or exceeds AgERA5’s performance. The study findings underscore the importance of evaluating metanalysis datasets in the application area before their use for precision agriculture, particularly in regions with complex topography. Full article
(This article belongs to the Section Biometeorology and Bioclimatology)
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17 pages, 6128 KiB  
Article
Spatiotemporal Characteristics of Mesoscale Convective Systems in the Yangtze River Delta Urban Agglomeration and Their Response to Urbanization
by Xinguan Du, Tianwen Sun and Kyaw Than Oo
Atmosphere 2025, 16(3), 245; https://doi.org/10.3390/atmos16030245 - 21 Feb 2025
Viewed by 496
Abstract
Mesoscale convective systems (MCSs) are major contributors to extreme precipitation in urban agglomerations, exhibiting complex characteristics influenced by large-scale climate variability and local urban processes. This study utilizes a high-resolution MCS database spanning from 2001 to 2020 to investigate the spatiotemporal variations of [...] Read more.
Mesoscale convective systems (MCSs) are major contributors to extreme precipitation in urban agglomerations, exhibiting complex characteristics influenced by large-scale climate variability and local urban processes. This study utilizes a high-resolution MCS database spanning from 2001 to 2020 to investigate the spatiotemporal variations of MCSs in the Yangtze River Delta (YRD) urban agglomeration and assess their response to urbanization. Our analysis reveals significant spatial and temporal differences in MCS activities during the warm season (April to September), including initiation, movement, and lifespan, with notable trends observed over the study period. MCSs are found to contribute substantially to hourly extreme precipitation, accounting for approximately 60%, which exceeds their contribution to total precipitation. Furthermore, the role of MCSs in extreme precipitation has also increased, driven by the intensification of MCS-induced extreme rainfall. Additionally, MCS characteristics exhibit significant regional differences. Urban areas experience more pronounced changes in MCS activity and precipitation compared to the surrounding rural regions. Specifically, urbanization contributes approximately 16% to MCS-related precipitation and 19% to MCS initiation, highlighting its substantial role in enhancing these processes. Moreover, mountainous areas and water bodies surrounding cities show stronger trends in certain MCS characteristics than urban and rural plains. This may be attributed to climatological conditions that favor MCS activity in these regions, as well as the complex interactions between urbanization, topography, and land–sea contrasts. These complicated dynamics warrant further investigation to better understand their implications. Full article
(This article belongs to the Section Meteorology)
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15 pages, 7070 KiB  
Article
Assessment of Fire Dynamics in the Amazon Basin Through Satellite Data
by Humberto Alves Barbosa, Catarina Oliveira Buriti and Tumuluru Venkata Lakshmi Kumar
Atmosphere 2025, 16(2), 228; https://doi.org/10.3390/atmos16020228 - 18 Feb 2025
Cited by 1 | Viewed by 1252
Abstract
The Amazon region is becoming more vulnerable to wildfires occurring in the dry season, a crisis amplified by climate change, which affects biomass burning across a wide range of forest environments. In this study, we examined the impact of seasonal fire on greenhouse [...] Read more.
The Amazon region is becoming more vulnerable to wildfires occurring in the dry season, a crisis amplified by climate change, which affects biomass burning across a wide range of forest environments. In this study, we examined the impact of seasonal fire on greenhouse (GHG) emissions over the study region during the last two decades of the 21st century by integrating calibrated and validated satellite-derived products of estimations of burned biomass area, land cover, vegetation greenness, rainfall, land surface temperature (LST), carbon monoxide (CO), and nitrogen dioxide (NO2) through geospatial techniques. The results revealed a strong impact of fire activity on GHG emissions, with abrupt changes in CO and NO2 emission factors between early and middle dry season fires (July–September). Among these seven variables analyzed, we found a positive relationship between the total biomass burned area and fire-derived GHG emission factors (r2 = 0.30) due to the complex dynamics of plant moisture and associated CO and NO2 emissions generated by fire. Nevertheless, other land surface drivers showed the weakest relationships (r2~0.1) with fire-derived GHG emissions due to other factors that drive their regional distribution. Our analysis suggests the importance of continued research on the response of fire season to other land surface characteristics that represent the processes driving fire over the study region such as fuel load, composition, and structure, as well as prevailing weather conditions. These determinants drive fire-related GHG emissions and fire-related carbon cycling relationships and can, therefore, appropriately inform policy fire-abatement guidelines. Full article
(This article belongs to the Section Air Quality)
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36 pages, 9488 KiB  
Article
New Challenges for Tropical Cyclone Track and Intensity Forecasting in Unfavorable External Environment in Western North Pacific. Part I. Formations South of 20° N
by Russell L. Elsberry, Hsiao-Chung Tsai, Wen-Hsin Huang and Timothy P. Marchok
Atmosphere 2025, 16(2), 226; https://doi.org/10.3390/atmos16020226 - 18 Feb 2025
Viewed by 797
Abstract
A pre-operational test started in mid-July 2024 to demonstrate the capability of the ECMWF’s ensemble (ECEPS) to predict western North Pacific Tropical Cyclones (TCs) lifecycle tracks and intensities revealed new forecasting challenges for four typhoons that started well south of 20° N. As [...] Read more.
A pre-operational test started in mid-July 2024 to demonstrate the capability of the ECMWF’s ensemble (ECEPS) to predict western North Pacific Tropical Cyclones (TCs) lifecycle tracks and intensities revealed new forecasting challenges for four typhoons that started well south of 20° N. As Typhoon Gaemi (05 W) was moving poleward into an unfavorable environment north of 20° N, a sharp westward turn to cross Taiwan was a challenge to forecast. The pre-Yagi (12 W) westward turn across Luzon Island, re-formation, and then extremely rapid intensification prior to striking Hainan Island were challenges to forecast. The slow intensification of Bebinca (14 W) after moving poleward across 20° N into an unfavorable environment was better forecast by the ECEPS than by the Joint Typhoon Warning Center (JTWC), which consistently over-predicted the intensification. An early westward turn south of 20° N by Kong-Rey (23 W) leading to a long westward path along 17° N and then a poleward turn to strike Taiwan were all track forecasting challenges. Four-dimensional COAMPS-TC Dynamic Initialization analyses utilizing high-density Himawari-9 atmospheric motion vectors are proposed to better define the TC intensities, vortex structure, and unfavorable environment for diagnostic studies and as initial conditions for regional model predictions. In Part 2 study of selected 2024 season TCs that started north of 20° N, more challenging track forecasts and slow intensification rates over an unfavorable TC environment will be documented. Full article
(This article belongs to the Special Issue Typhoon/Hurricane Dynamics and Prediction (2nd Edition))
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30 pages, 32662 KiB  
Article
Air Pollution Trends and Predictive Modeling for Three Cities with Different Characteristics Using Sentinel-5 Satellite Data and Deep Learning
by Salma Alkayal, Hind Almisbahi, Souad Baowidan and Entisar Alkayal
Atmosphere 2025, 16(2), 211; https://doi.org/10.3390/atmos16020211 - 13 Feb 2025
Viewed by 1158
Abstract
Accurate air quality forecasting is important in pollution prevention and risk reduction. Effective short-term and long-term forecasting models are needed. This study investigated the need for a new model to forecast air pollution concentrations in three cities with distinct characteristics: a city with [...] Read more.
Accurate air quality forecasting is important in pollution prevention and risk reduction. Effective short-term and long-term forecasting models are needed. This study investigated the need for a new model to forecast air pollution concentrations in three cities with distinct characteristics: a city with high industrial activity, a city with a high population density and urbanization, and an agricultural city. The air pollution data were collected using the Sentinel-5P satellite and Google Earth Engine to apply descriptive analysis and comparison of two years, 2022 and 2023. The studied cities were Al Riyadh (high population), Al Jubail (industrial), and Najran (agricultural) in Saudi Arabia. The selected pollutants were SO2, NO2, CO, O3, and HCHO. In addition, this study investigated the variations observed in all the pollutants during the months of the year, the correlations between the contaminants, and the correlation between NO2 and the meteorological data. Based on our findings, Al Jubail had the highest level of all the pollutants during the two years, except for NO2, for which the highest level was observed in Al Riyadh, which has witnessed notable urbanization and development recently. Moreover, this study developed a forecasting model for the concentration of NO2 based on weather data and the previous values of NO2 using Long Short-Term Memory (LSTM) and Time2Vec. The modeling proved that any model that is trained on data collected from a specific city is not suitable for predicting the pollution level in another city and the level of another pollutant, as the three cities have different correlations with the pollutants and the weather data. The proposed model demonstrated a superior accuracy in predicting NO2 concentrations compared to traditional LSTM models, effectively capturing temporal patterns and achieving minimal prediction errors, which contributes to ongoing efforts to understand the dynamics of air pollution based on cities’ characteristics and the period of the year. Full article
(This article belongs to the Special Issue Dispersion and Mitigation of Atmospheric Pollutants)
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22 pages, 11030 KiB  
Article
Adjusting Soil Temperatures with a Physics-Informed Deep Learning Model for a High-Resolution Numerical Weather Prediction System
by Qiufan Wang, Yubao Liu, Yueqin Shi and Shaofeng Hua
Atmosphere 2025, 16(2), 207; https://doi.org/10.3390/atmos16020207 - 12 Feb 2025
Viewed by 806
Abstract
Soil temperature (ST) plays an important role in the surface heat energy balance, and an accurate description of soil temperatures is critical for numerical weather prediction; however, it is difficult to consistently measure soil temperatures. We developed a U-Net-based deep learning model to [...] Read more.
Soil temperature (ST) plays an important role in the surface heat energy balance, and an accurate description of soil temperatures is critical for numerical weather prediction; however, it is difficult to consistently measure soil temperatures. We developed a U-Net-based deep learning model to derive soil temperatures (designated as ST-U-Net) primarily based on 2 m air temperature (T2) forecasts. The model, the domain of which covers the Mt. Lushan region, was trained and tested by utilizing the high-resolution forecast archive of an operational weather research and forecasting four-dimensional data assimilation (WRF-FDDA) system. The results showed that ST-U-Net can accurately estimate soil temperatures based on T2 inputs, achieving a mean absolute error (MAE) of less than 0.8 K on the testing set of 5055 samples. The performance of ST-U-Net varied diurnally, with smaller errors at night and slightly larger errors in the daytime. Incorporating additional inputs such as land uses, terrain height, radiation flux, surface heat flux, and coded time further reduced the MAE for ST by 26.7%. By developing a boundary-layer physics-guided training strategy, the error was further reduced by 8.8%. Full article
(This article belongs to the Section Meteorology)
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19 pages, 4707 KiB  
Article
The Impact of Lightning Rods on the Differential Reflectivity of X-Band Radar
by Hui Wang, Haifeng Yu, Hao Wen and Zhifeng Shu
Atmosphere 2025, 16(2), 204; https://doi.org/10.3390/atmos16020204 - 11 Feb 2025
Viewed by 532
Abstract
Lightning rod configuration is crucial in radar stations. With widespread application of dual-polarisation technology, lightning rods have a significant impact on radar differential reflectivity, particularly for X-band radars with shorter wavelengths. Quantitative analyses and methods for reducing the impact of lightning rods on [...] Read more.
Lightning rod configuration is crucial in radar stations. With widespread application of dual-polarisation technology, lightning rods have a significant impact on radar differential reflectivity, particularly for X-band radars with shorter wavelengths. Quantitative analyses and methods for reducing the impact of lightning rods on radar data quality have become particularly important. In this study, lightning rods of two different sizes were configured on Beijing’s Fangshan X-band radar to perform antenna far-field tests and precipitation process comparative observation tests, and to conduct a quantitative impact assessment of the antenna electrical performance parameters and radar differential reflectivity. First, far-field tests were conducted on the impact of small- and original-diameter lightning rods on the Fangshan X-band radar. The results showed that the horizontal polarisation beam width was reduced by 0.081 and 0.08°, while the vertical polarisation beam width was reduced by 0.02 and 0.11°, respectively. Second, light rain or snowfall with a signal-to-noise ratio greater than 15 dB, and a correlation coefficient greater than 0.985, were selected for comparative observation. When other environmental influences could not be isolated, the original lightning rod showed a maximum ZDR value of 1.32 dB and a maximum azimuth span of 35°. The maximum ZDR value of the small-diameter lightning rod was 0.18 dB and the maximum azimuth span was 20°; however, its deviation from the theoretical maximum value is only 0.05 dB. Therefore, once the system configuration is determined, the design of an appropriate lightning rod scheme can effectively improve radar data quality. Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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29 pages, 3568 KiB  
Article
Threshold Effects of the Interaction Between Urban Development and Atmospheric Pollution
by Xiaoling Yuan, Hanyu Geng and Zhaopeng Li
Atmosphere 2025, 16(2), 201; https://doi.org/10.3390/atmos16020201 - 10 Feb 2025
Viewed by 703
Abstract
Over the past 70 years since the founding of the People’s Republic of China, urban development has achieved remarkable progress but also encountered severe atmospheric pollution, which has become a significant obstacle to high-quality urban development. Understanding the interaction mechanisms between urban development [...] Read more.
Over the past 70 years since the founding of the People’s Republic of China, urban development has achieved remarkable progress but also encountered severe atmospheric pollution, which has become a significant obstacle to high-quality urban development. Understanding the interaction mechanisms between urban development and atmospheric pollution is thus crucial for promoting sustainable urban construction. This paper explores these mechanisms by analyzing the interplay between urban population, industry, space, social development, and pollution through a theoretical framework. Using a simultaneous equations model and the Three-Stage Least Squares (3SLS) method, it examines these relationships and further investigates threshold effects. The findings reveal a nonlinear relationship with significant thresholds: (1) High levels of PM2.5, population size, and industrial agglomeration can shift from exacerbating pollution to enabling governance, though excessive thresholds reverse this trend. (2) PM2.5 mediates the impact of spatial sprawl, environmental regulation, and population dynamics, oscillating between governance and pollution effects. (3) Industrial agglomeration and spatial sprawl show variable impacts on pollution mitigation depending on pollution intensity and urban thresholds. These findings provide critical insights into the intricate dynamics between urban development and atmospheric pollution, emphasizing the importance of adopting differentiated strategies based on specific urban thresholds. Ultimately, this research contributes to the broader goal of harmonizing economic growth, social development, and environmental sustainability in urban areas, serving as a valuable reference for cities worldwide facing similar challenges. Full article
(This article belongs to the Special Issue Air Pollution in China (3rd Edition))
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18 pages, 5015 KiB  
Article
Dissipation Scaling with a Variable Cϵ Coefficient in the Stable Atmospheric Boundary Layer
by Marta Wacławczyk, Jackson Nzotungishaka, Paweł Jędrejko, Joydeep Sarkar and Szymon P. Malinowski
Atmosphere 2025, 16(2), 188; https://doi.org/10.3390/atmos16020188 - 7 Feb 2025
Viewed by 561
Abstract
This work concerns the Taylor formula for the turbulence kinetic energy dissipation rate in the stable atmospheric boundary layer. The formula relates the turbulence kinetic energy dissipation rate to statistics at large scales, namely, the turbulence kinetic energy and the integral length scale. [...] Read more.
This work concerns the Taylor formula for the turbulence kinetic energy dissipation rate in the stable atmospheric boundary layer. The formula relates the turbulence kinetic energy dissipation rate to statistics at large scales, namely, the turbulence kinetic energy and the integral length scale. In parameterization schemes for atmospheric turbulence, it is usually assumed that the dissipation coefficient Cϵ in the Taylor formula is constant. However, a series of recent theoretical works and laboratory experiments showed that Cϵ depends on the local Reynolds number. We calculate turbulence statistics, including the dissipation rate, the standard deviation of fluctuating velocities and integral length scales, using observational data from the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition. We show that the dissipation coefficient Cϵ varies considerably and is a function of the Reynolds number, however, the functional form of this dependency in the stably stratified atmospheric boundary layer is different than in previous studies. Full article
(This article belongs to the Special Issue Atmospheric Boundary Layer Processes, Characteristics and Parameterization (3rd Edition))
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20 pages, 5287 KiB  
Article
Research on NOx Emissions Testing and Optimization Strategies for Diesel Engines Under Low-Load Cycles
by Fengbin Wang, Jianfu Zhao, Tengteng Li, Peng Guan, Shuangxi Liu, Haiqiao Wei and Lei Zhou
Atmosphere 2025, 16(2), 190; https://doi.org/10.3390/atmos16020190 - 7 Feb 2025
Cited by 1 | Viewed by 1055
Abstract
Under low-load cycles (LLCs), the issue of high NOx emissions from diesel engines is attracting widespread attention. Through a combination of experimental and simulation approaches, the NOx emission behavior under LLC conditions was investigated. Furthermore, the optimization strategies for reducing NOx emissions was [...] Read more.
Under low-load cycles (LLCs), the issue of high NOx emissions from diesel engines is attracting widespread attention. Through a combination of experimental and simulation approaches, the NOx emission behavior under LLC conditions was investigated. Furthermore, the optimization strategies for reducing NOx emissions was studied based on a dual selective catalytic reduction (SCR) after-treatment system. The results indicate that emissions at load rates below 30% during LLCs account for more than 67.5% of the total cycle emissions, particularly under idling and start-stop conditions. Moreover, it was found that NOx emissions decrease significantly by using a pre-positioned dual SCR after-treatment system. And, the closer the SCR is to the engine, the higher the NOx conversion efficiency becomes. As the SCR’s position is adjusted, the rate of NOx removal stabilizes, achieving a maximum reduction in NOx concentration of up to 60.1%. Full article
(This article belongs to the Section Air Pollution Control)
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