Atmosphere

15 pages, 7703 KiB

Open AccessEditor’s ChoiceArticle

Projections of Extreme Precipitation Changes over the Eastern Tibetan Plateau: Exploring Thermodynamic and Dynamic Contributions

by Xiaojiang Liu, Xi Liu, Chengxin Li, Xiaomin Ma, Kena Chen, Zhenhong Sun, Kangning Wang, Quanliang Chen and Hongke Cai

Atmosphere 2025, 16(6), 664; https://doi.org/10.3390/atmos16060664 - 31 May 2025

Viewed by 246

Abstract

The Eastern Tibetan Plateau (ETP), characterized by its intricate topography and pronounced altitudinal gradient, presents significant challenges for climate model simulations. This study assesses precipitation over the ETP using high-resolution (HR) and low-resolution (LR) models from CMIP6 HighResMIP. Both HR and LR models [...] Read more.

The Eastern Tibetan Plateau (ETP), characterized by its intricate topography and pronounced altitudinal gradient, presents significant challenges for climate model simulations. This study assesses precipitation over the ETP using high-resolution (HR) and low-resolution (LR) models from CMIP6 HighResMIP. Both HR and LR models successfully reproduce the spatial distribution of annual precipitation, capturing the northwest-to-southeast increasing gradient. However, HR models significantly outperform LR models, reducing the annual mean precipitation bias from 1.09 mm/day to 1.00 mm/day (9% reduction, p < 0.05, two-tailed Student’s t-test) and decreasing RMSE by 12% (p < 0.05) in the ETP for the 1985–2014 period. Furthermore, HR models exhibit superior skill in simulating extreme precipitation events, particularly over the Sichuan Basin. For the 1985–2014 period, HR models show markedly smaller biases in representing extreme precipitation and accurately reflect observed trends. Projections for the future suggest a pronounced intensification of extreme precipitation events across the region. Process-based scaling diagnostics attribute these changes predominantly to dynamical components, which account for approximately 85% of the total scaling change in HR models and 89% in LR models. These findings underscore the pivotal role of dynamical processes in shaping extreme precipitation and highlight the advantages of HR models in enhancing simulation fidelity. This study provides critical insights into climate model performance, offering robust information to inform climate mitigation and adaptation strategies tailored for the ETP. Full article

(This article belongs to the Section Meteorology)

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19 pages, 8563 KiB

Open AccessEditor’s ChoiceArticle

RANS and LES Simulations of Localized Pollutant Dispersion Around High-Rise Buildings Under Varying Temperature Stratifications

by Jinrong Zhao, Dongpeng Guo, Zhehai Zhang, Jiayi Guo, Yunpeng Li, Junfang Zhang and Xiaofan Wang

Atmosphere 2025, 16(6), 661; https://doi.org/10.3390/atmos16060661 - 31 May 2025

Viewed by 281

Abstract

This research investigates the influence of buildings on the flow pattern and pollutant spread under different temperature stratification scenarios. Using Reynolds-averaged Navier–Stokes (RANS) equations alongside the large eddy simulation (LES) model, the findings were validated through comparisons with wind tunnel experiments. Results indicate [...] Read more.

This research investigates the influence of buildings on the flow pattern and pollutant spread under different temperature stratification scenarios. Using Reynolds-averaged Navier–Stokes (RANS) equations alongside the large eddy simulation (LES) model, the findings were validated through comparisons with wind tunnel experiments. Results indicate that the return zone length on the leeward side of the building is the longest, around 1.75 times the building height (H) when the Richardson number (Ri_b) is 0.08. This return zone length reduces to approximately 1.4 H when Ri_b is 0.0 and further decreases to 1.25 H with a Ri_b of −0.1. Pollutant dispersion is similarly affected by the flow field, which aligns with these trends. The studied models revealed that LES proved the most accurate, closely matching wind tunnel results across all temperature stratification levels, while RANS overestimated values at building height (z/H = 1.0) and around the building (x/H < 0.625). To balance computational efficiency with prediction accuracy, a hybrid method integrating LES and RANS is recommended. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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22 pages, 6138 KiB

Open AccessEditor’s ChoiceArticle

Simulating Near-Surface Winds in Europe with the WRF Model: Assessing Parameterization Sensitivity Under Extreme Wind Conditions

by Minkyu Lee, Donggun Oh, Jin-Young Kim and Chang Ki Kim

Atmosphere 2025, 16(6), 665; https://doi.org/10.3390/atmos16060665 - 31 May 2025

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Abstract

Accurately simulating near-surface wind speeds is indispensable for wind energy development, particularly under extreme weather conditions. This study utilizes the Weather Research and Forecasting (WRF) model with a 6 km resolution to evaluate 80 m wind speed simulations over Europe, using the ECMWF [...] Read more.

Accurately simulating near-surface wind speeds is indispensable for wind energy development, particularly under extreme weather conditions. This study utilizes the Weather Research and Forecasting (WRF) model with a 6 km resolution to evaluate 80 m wind speed simulations over Europe, using the ECMWF (European Centre for Medium-Range Weather Forecasts) reanalysis version 5 (ERA5) as initial and lateral boundary conditions. Two cases were analyzed: a normal case with relatively weak winds, and an extreme case with intense cyclonic activity over 7 days, focusing on offshore wind farm regions and validated against Forschungsplattformen in Nord- und Ostsee (FINO) observational data. Sensitivity experiments were conducted by modifying key physical parameterizations associated with wind simulation to assess their impact on accuracy. Results reveal that while the model realistically captured temporal wind speed variations, errors were significantly amplified in extreme cases, with overestimation in weak wind regimes and underestimation in strong winds (approximately 1–3 m/s). The Asymmetrical Convective Model 2 (ACM2) planetary boundary layer (PBL) scheme demonstrated superior performance in extreme cases, while there were no significant differences among experiments under normal cases. These findings emphasize the critical role of physical parameterizations and the need for improved modeling approaches under extreme wind conditions. This research contributes to developing reliable wind speed simulations, supporting the operational stability of wind energy systems. Full article

(This article belongs to the Section Meteorology)

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15 pages, 5721 KiB

Open AccessEditor’s ChoiceCommunication

A Meteorological Analysis of the Missed Approach of an Aircraft at Taoyuan International Airport, Taiwan, During Typhoon Kong-Rey in 2024—The Impact of Crosswind and Turbulence

by Pak Wai Chan, Yan Yu Leung and Kai Kwong Lai

Atmosphere 2025, 16(6), 660; https://doi.org/10.3390/atmos16060660 - 30 May 2025

Viewed by 886

Abstract

When Typhoon Kong-rey hit Taiwan in October 2024, an aircraft attempting to land at Taoyuan International Airport undertook a missed approach and landed successfully on the second attempt. The possible meteorological factors causing this missed approach are studied in this study based on [...] Read more.

When Typhoon Kong-rey hit Taiwan in October 2024, an aircraft attempting to land at Taoyuan International Airport undertook a missed approach and landed successfully on the second attempt. The possible meteorological factors causing this missed approach are studied in this study based on a methodology specifically adopted for Hong Kong International Airport; namely, studying crosswind as derived from aircraft and airport meteorological observations, as well as the low-level turbulence derived from data on the aircraft’s vertical acceleration and high-resolution numerical weather prediction model results. A significant crosswind component and a gusting crosswind are the major reasons for the missed approach. The low-level turbulence appears to have been secondary/minor, as shown by the successful landings of aircraft before and after the event. It is concluded that the methodology supporting airport operations in Hong Kong may be used to explain missed approach cases at other airports under the influence of tropical cyclones. Full article

(This article belongs to the Special Issue Advance in Transportation Meteorology (3rd Edition))

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11 pages, 1433 KiB

Open AccessEditor’s ChoiceArticle

The Effects of Nonplanar Cloud Top on Lightning Optical Observations from Space-Based Instruments

by Bingzhe Dai, Qilin Zhang and Xingke Pan

Atmosphere 2025, 16(6), 657; https://doi.org/10.3390/atmos16060657 - 29 May 2025

Viewed by 245

Abstract

Satellite optical observations of lightning are influenced by a variety of factors. Studying these factors can provide valuable reference information for applications such as lightning parameter inversion. However, due to the variability of natural factors and the high cost of field observations, research [...] Read more.

Satellite optical observations of lightning are influenced by a variety of factors. Studying these factors can provide valuable reference information for applications such as lightning parameter inversion. However, due to the variability of natural factors and the high cost of field observations, research requiring controlled variables often relies heavily on effective simulation models. To this end, we applied our developed optical transmission model for lightning, which can simultaneously account for the spatiotemporal characteristics of lightning sources and observation angles, as well as inhomogeneous and irregular cloud environments, to analyze an unexplained hypothesis from previous studies—that non-planar cloud tops may also be an influencing factor. Our analysis confirms that non-planar cloud tops are indeed an important factor that must be considered, especially under smaller or larger observation angles. In the simulation results, undulations caused an energy increase of up to 43.19% at a 0° observation angle, while at a 60° observation angle, the undulations resulted in an additional attenuation of approximately 17.5%. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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19 pages, 3022 KiB

Open AccessEditor’s ChoiceArticle

Research on Time Series Interpolation and Reconstruction of Multi-Source Remote Sensing AOD Product Data Using Machine Learning Methods

by Huifang Wang, Min Wang, Pan Jiang, Fanshu Ma, Yanhu Gao, Xinchen Gu and Qingzu Luan

Atmosphere 2025, 16(6), 655; https://doi.org/10.3390/atmos16060655 - 28 May 2025

Viewed by 392

Abstract

The satellite remote sensing of Aerosol Optical Depth (AOD) products is crucial in environmental monitoring and atmospheric pollution research. However, data gaps in AOD products from satellites like Fengyun significantly hinder continuous, seamless environmental monitoring capabilities, posing challenges for the long-term analysis of [...] Read more.

The satellite remote sensing of Aerosol Optical Depth (AOD) products is crucial in environmental monitoring and atmospheric pollution research. However, data gaps in AOD products from satellites like Fengyun significantly hinder continuous, seamless environmental monitoring capabilities, posing challenges for the long-term analysis of atmospheric pollution trends, responses to sudden ecological events, and disaster management. This study aims to develop a high-precision method to fill spatial AOD missing values and generate daily full-coverage AOD products for the Beijing–Tianjin–Hebei region in 2021 by integrating multi-dimensional data, including meteorological models, multi-source remote sensing, surface conditions, and nighttime light parameters, and applying machine learning methods. A comparison of five machine learning models showed that the random forest model performed optimally in AOD inversion, achieving a root mean square error (RMSE) of 0.11 and a coefficient of determination (R²) of 0.93. Seasonal evaluation further indicated that the model’s simulation was best in winter. Variable importance analysis identified relative humidity (RH) as the most critical factor influencing model results. The reconstructed full-coverage AOD product exhibited a spatial distribution trend of significantly higher values in the southern plain areas compared to mountainous regions, consistent with the actual aerosol distribution patterns in the Beijing–Tianjin–Hebei area. Moreover, the product demonstrated overall smoothness and high accuracy. This research lays the foundation for establishing a long-term, 1 km resolution, daily spatially continuous AOD product for the Beijing–Tianjin–Hebei region and beyond, providing more robust data support for addressing regional and larger-scale environmental challenges. Full article

(This article belongs to the Section Aerosols)

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31 pages, 29953 KiB

Open AccessEditor’s ChoiceArticle

Urban Impacts on Convective Squall Lines over Chicago in the Warm Season—Part II: A Numerical Study of Urban Infrastructure Effects on the Evolution of City-Scale Convection

by S. M. Shajedul Karim, Michael L. Kaplan and Yuh-Lang Lin

Atmosphere 2025, 16(6), 652; https://doi.org/10.3390/atmos16060652 - 27 May 2025

Viewed by 314

Abstract

Numerical models were employed to simulate the effects of urban infrastructure on the city-scale precipitation distribution during multiple closely occurring convective squall line events over Chicago. Two high-resolution simulations were inter-compared, one using standard land use databases to initialize the WRF-ARW numerical model [...] Read more.

Numerical models were employed to simulate the effects of urban infrastructure on the city-scale precipitation distribution during multiple closely occurring convective squall line events over Chicago. Two high-resolution simulations were inter-compared, one using standard land use databases to initialize the WRF-ARW numerical model and the other using a high-resolution urban canopy formulation and detailed land use databases to initialize the WRF-UCM numerical model. Two squall lines organized and propagated over Chicago during an eight-hour period. The (1 km) spatio-temporal evolution of the first squall line was more accurately simulated by the WRF-UCM than that simulated by the WRF-ARW. The WRF-UCM captures more realistic urban heat island-induced buoyancy forcing when validated against multiple airport meteograms and Doppler radar-derived reflectivity and precipitation. The WRF-UCM increases surface heating, substantially strengthening the surface-based convective available potential energy (SBCAPE) and subsequent cold downdrafts. Additionally, the increased surface heating acts to strengthen and bifurcate the upper-level divergence and energize three low-level jets that converge upon the city and shape the convective organization. While the effect of this additional buoyancy on the first squall line was critical, the second line’s dissipation was not substantially different in the two simulations because of diminishing tropospheric forcing. Full article

(This article belongs to the Section Meteorology)

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22 pages, 7003 KiB

Open AccessEditor’s ChoiceArticle

Output of Volcanic SO₂ Gases and Their Dispersion in the Atmosphere: The Case of Vulcano Island, Aeolian Archipelago, Italy

by Fabio Vita, Benedetto Schiavo, Claudio Inguaggiato, Jacopo Cabassi, Stefania Venturi, Franco Tassi and Salvatore Inguaggiato

Atmosphere 2025, 16(6), 651; https://doi.org/10.3390/atmos16060651 - 27 May 2025

Viewed by 420

Abstract

Gases emitted from active volcanic systems constitute a primary natural source of global atmospheric pollution. Atmospheric sulfur dioxide (SO₂) concentrations were monitored using a near-continuous network based on Scan-DOAS (Differential Optical Absorption Spectroscopy) technology. Complementary intermittent measurements were performed using a [...] Read more.

Gases emitted from active volcanic systems constitute a primary natural source of global atmospheric pollution. Atmospheric sulfur dioxide (SO₂) concentrations were monitored using a near-continuous network based on Scan-DOAS (Differential Optical Absorption Spectroscopy) technology. Complementary intermittent measurements were performed using a UV Thermo^® analyzer deployed at fixed locations and along predefined transects on the island. SO₂ flux data derived from the Scan-DOAS measurements, coupled with atmospheric dispersion maps generated using the AERMOD modeling software, enabled the estimation of SO₂ distribution across the volcanic crater region and inhabited areas of the island, including Vulcano Village and Vulcano Piano. The results of the estimation of SO₂ concentration in the atmosphere, integrated with the dispersion modeling, exhibited consistency with direct SO₂ concentration measurements obtained by the Thermo^® analyzer, demonstrating coherence between the two methodologies, although some overestimations of ambient SO₂ were noted. This study provided valuable insights into areas with anomalous SO₂ concentrations exceeding the threshold limits established by the World Health Organization (WHO) and the European Union (EU). These limits are generally exceeded in the crater zone and surrounding areas. The findings also highlighted the influence of prevailing winds and the temporal variations in volcanic degassing activity observed over the preceding 17 years, characterized by four periods of unrest degassing with SO₂ emission rates from the summit solfataric area reaching up to 250 tonnes per day (td⁻¹). Full article

(This article belongs to the Special Issue Natural Sources Aerosol Remote Monitoring (2nd Edition))

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12 pages, 592 KiB

Open AccessEditor’s ChoiceArticle

Estimation of the Annual Greenhouse Gas Emissions from the Town Gas Distribution System in Hong Kong in 2022

by Daisong Chen, Tsz Lap Chan and Jin Shang

Atmosphere 2025, 16(6), 643; https://doi.org/10.3390/atmos16060643 - 26 May 2025

Viewed by 327

Abstract

Estimating leaks in urban gas distribution systems is crucial for reducing greenhouse gas emissions from fugitive losses and mitigating costly waste. This study aimed to use a simplified methodology to estimate pipeline leakage in gas distribution systems and validate these estimations against established [...] Read more.

Estimating leaks in urban gas distribution systems is crucial for reducing greenhouse gas emissions from fugitive losses and mitigating costly waste. This study aimed to use a simplified methodology to estimate pipeline leakage in gas distribution systems and validate these estimations against established benchmarks or other gases globally. The estimation encompassed sources including third-party damage, long-term permeation, flaring, and purging during pipeline commissioning and decommissioning, as well as fugitive leakage, each requiring respective evaluation. Results showed that the total town gas leakage volume was around 695,044 m³ to 2,009,991 m³, accounting for 0.045% to 0.13% of the total town gas sales in 2022. Among the five leakage sources, fugitive leakage was the major contributor with the leakage volume of 1,938,914 m³. To comprehensively benchmark all emission factors (EFs), those from previously reported studies were adapted to the town gas scenario and combined with the current activity factors (AFs) in Hong Kong to calculate the leakage amounts. Comparing our results with different models, we observed variations in estimated leakage amounts based on years, regions, and sampling methods. Upgrades in pipeline materials led to reduced EFs and subsequently lower total gas leakage. Our findings support efforts to reduce greenhouse gas emissions by providing actionable data for policymakers and utility companies to address gas leakage issues. Full article

(This article belongs to the Section Air Pollution Control)

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22 pages, 21792 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of Automated Spread–F (SF) Detection over the Midlatitude Ionosphere

by Krishnendu Sekhar Paul, Trisani Biswas and Haris Haralambous

Atmosphere 2025, 16(6), 642; https://doi.org/10.3390/atmos16060642 - 25 May 2025

Viewed by 306

Abstract

The present study evaluates an automated Spread–F (SF_P) detection algorithm by integrating SF-related (QF, FF) and ionospheric parameters (hmF2, h’F), acting as an indicator for SF events, from SAO Explorer auto-scaled (ARTIST) data, compared to manually identified SF events ( [...] Read more.

The present study evaluates an automated Spread–F (SF_P) detection algorithm by integrating SF-related (QF, FF) and ionospheric parameters (hmF2, h’F), acting as an indicator for SF events, from SAO Explorer auto-scaled (ARTIST) data, compared to manually identified SF events (SF_M) across nine European midlatitude ionospheric stations. The stations were categorized into four latitude sectors to evaluate latitudinal influence in an analysis within the period 2009–2021 from low to high solar activity levels. The results revealed an inverse correlation between solar activity and agreement between SF_P and SF_M, with stronger agreement during the solar minimum. In the 55°–60° N sector, the SF_P–SF_M match varied from 71% during the solar minimum to 47% during the solar maximum, with overestimation associated with LSTID activity. In the 50°–55° N sector, agreement ranged from 66% to 56%, with overestimation associated with MSTIDs and oblique traces. The 40°–45° N sector exhibited the highest variability (89% to 42%), where Satellite Traces (STs), Multiple Reflected Echoes (MREs), and spread Es led to both over– and underestimations. In the 35°–40° N sector, agreement dropped to 30% during the solar maximum, with wintertime overestimation and summer underestimation significantly characterized by STs, MREs, and Es–layer interference. Full article

(This article belongs to the Special Issue Global Space Weather Variability with a Specific Focus on Ionospheric Climatological Forecasting and Predictive Modelling)

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18 pages, 2642 KiB

Open AccessEditor’s ChoiceArticle

Urbanization Changes the Composition of Airborne Fungi and Increases the Proportion of Fungal Allergens—A Case Study in Shanghai, China

by Ke Yan, Ying Chen, Mingtao Zhao, Yifei Li and Jiaxin He

Atmosphere 2025, 16(6), 641; https://doi.org/10.3390/atmos16060641 - 24 May 2025

Viewed by 275

Abstract

Urbanization has been suspected to increase the allergic rate of people, and its impact on airborne fungi and potential allergens has drawn attention. In this study, aerosol samples were collected concurrently at proximate urban and rural sites of Shanghai during the four seasons [...] Read more.

Urbanization has been suspected to increase the allergic rate of people, and its impact on airborne fungi and potential allergens has drawn attention. In this study, aerosol samples were collected concurrently at proximate urban and rural sites of Shanghai during the four seasons to analyze the changes in abundance and community composition of airborne fungi. In summer, there were significantly higher concentrations of fungi in the urban atmosphere compared to at the rural site. Ascomycota and Basidiomycota were the top two fungal phyla, and Cladosporium was the most abundant genus year round. Alternaria was the second highest genus in spring and winter (only the rural site), whereas Nigrospora ranked second during summer and autumn due to it largely being sourced from marine organisms and predominantly marine-influenced air masses in these seasons. Airborne fungal richness was relatively higher at the rural site than in urban during winter. Allergenic fungal species were found to be more abundant in winter than in other seasons; particularly, the relative abundance of Cladosporium sp. was significantly higher (p < 0.001), and Fusarium culmorum and Cladosporium herbarum also increased more in urban than in rural areas, which may be one of the key factors contributing to the rising allergic rate in the urban population. Full article

(This article belongs to the Section Aerosols)

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25 pages, 6210 KiB

Open AccessEditor’s ChoiceArticle

Prediction of Atmospheric Bioaerosol Number Concentration Based on PKO–AGA–SVM Fusion Algorithm and Fluorescence Lidar Telemetry

by Zhimin Rao, Yicheng Li, Jiandong Mao, Hu Zhao and Xin Gong

Atmosphere 2025, 16(6), 638; https://doi.org/10.3390/atmos16060638 - 23 May 2025

Viewed by 250

Abstract

In order to realize early warning prediction of the distribution characteristics of atmospheric bioaerosol content, this paper proposes using fluorescence lidar as a technical means to establish a prediction model of atmospheric bioaerosol concentration by obtaining the observation data set of bioaerosol concentration, [...] Read more.

In order to realize early warning prediction of the distribution characteristics of atmospheric bioaerosol content, this paper proposes using fluorescence lidar as a technical means to establish a prediction model of atmospheric bioaerosol concentration by obtaining the observation data set of bioaerosol concentration, combining it with the data set of atmospheric environmental parameters related to bioaerosol content, and utilizing the fusion algorithm PKO–AGA–SVM. The trained model was then used to predict the atmospheric bioaerosol concentration and compared with the bioaerosol concentration detected by fluorescence lidar to analyze the relative error of the model in predicting the bioaerosol number concentration with different algorithms as well as the bioaerosol number concentration at different pollution levels of atmospheric environmental quality. The experimental results show that the model prediction using the PKO–AGA–SVM fusion algorithm is better than the SVM, AGA–SVM, and PKO–SVM algorithms, with mean relative errors of 25.79, 20.75, 16.93, and 11.57%, respectively. Then, environmental data with different pollution levels were introduced for model prediction experiments, and the results show that the mean relative error of prediction was 12.75% when the air quality was excellent, the mean relative error of prediction was 13.01% when the air quality was good, the mean error of prediction was 10.53% when the air quality was mildly polluted, and the mean error of prediction was 13.72% when the air quality was moderately polluted. When the air quality was heavily polluted, the mean prediction error was 11.83%. The experimental results show that the prediction model has high accuracy and stability under different atmospheric conditions, which can provide a new research approach and technical support for the early warning system of atmospheric bioaerosol concentration. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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21 pages, 2500 KiB

Open AccessEditor’s ChoiceArticle

A Study of Theoretical Modeling for Scavenging Coefficients of Polydisperse Aerosols Removed by Rainfall

by Xing Gao, Can Qi, Hongqiang Wang and Hui Zhu

Atmosphere 2025, 16(6), 634; https://doi.org/10.3390/atmos16060634 - 22 May 2025

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Abstract

This paper incorporates various currently known collection mechanisms (including Brownian diffusion, interception effect, inertial impaction, thermophoresis, diffusiophoresis, and electrostatic interaction) into the calculation of the total collection efficiency to analyze their impacts on the scavenging coefficient. The turbulent effect is introduced into the [...] Read more.

This paper incorporates various currently known collection mechanisms (including Brownian diffusion, interception effect, inertial impaction, thermophoresis, diffusiophoresis, and electrostatic interaction) into the calculation of the total collection efficiency to analyze their impacts on the scavenging coefficient. The turbulent effect is introduced into the parametric study of the scavenging coefficient. Combining the local raindrop size distribution and aerosol size distribution, a theoretical prediction model for multi-fraction aerosol scavenging by rainfall is established and verified and corrected with measured data. The main conclusions are as follows: For particles within the accumulation mode range, the influence of the collision efficiency needs to be carefully considered. When studying the scavenging coefficient, it is necessary to combine the locally measured raindrop size distribution and aerosol size distribution. The influence of the aerosol size distribution on the scavenging coefficient under different seasonal conditions in the same area can be neglected. When the turbulent effect is introduced, the theoretical prediction is closer to the actual situation. In comparison with the actual measured PM_2.5 values in Guangzhou City, Hefei City, and Tianjin City, the temporal variation characteristics of PM_2.5 estimated by the theoretical model exhibit a substantial degree of consistency with the trends revealed by the measurement results. Additionally, a linear correlation is discernible between the scavenging coefficients obtained from field measurements in these three regions and those calculated by the theoretical model. Specifically, the equations of the linear relationships are Λ_s = 0.498 × 10⁻⁵ + 1.025Λ_m; Λ_s = 1.035Λ_m − 0.036 × 10⁻⁵; and Λ_s = 0.903Λ_m − 1.11 × 10⁻⁵. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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17 pages, 4672 KiB

Open AccessEditor’s ChoiceArticle

Identification and Correction for Sun Glint Contamination in Microwave Radiation Imager-Rainfall Mission Global Ocean Observations Onboard the FY-3G Satellite

by Qiumeng Xue, Xuanyuan Yang, Qiang Zhang and Zhenxing Liu

Atmosphere 2025, 16(6), 630; https://doi.org/10.3390/atmos16060630 - 22 May 2025

Viewed by 296

Abstract

Microwave radiometers are vital for global ocean observations, yet they are prone to errors from radio frequency interference, sun glint, and other contamination. This paper focuses on the newly launched Chinese FY-3G satellite’s Microwave Radiation Imager-Rainfall Mission (MWRI-RM) instrument, aiming to detect sun [...] Read more.

Microwave radiometers are vital for global ocean observations, yet they are prone to errors from radio frequency interference, sun glint, and other contamination. This paper focuses on the newly launched Chinese FY-3G satellite’s Microwave Radiation Imager-Rainfall Mission (MWRI-RM) instrument, aiming to detect sun glint contamination and set a critical angle for data quality control. The model regression difference method is employed to simulate uncontaminated brightness temperatures at 10.65 GHz. By comparing the observed and simulated values, this study finds that sun glint contamination, which causes a 0–5 K increase in brightness temperature, is strongly related to sun glint angle. Based on the statistical analysis of contaminated pixels from November 2023 to July 2024, it is recommended that a critical angle of 25° be used to flag contaminated areas. The method also identifies persistent television frequency interference along the U.S. coastline at 18.7 GHz, which the radio frequency interference (RFI) Flag in Level 1 data failed to detect. Through the utilization of the model regression difference method, the warm biases in the MWRI-RM observations can be corrected. This research offers a practical way to enhance the accuracy of the MWRI-RM data and can be applied to other microwave radiometry missions. Full article

(This article belongs to the Special Issue Satellite Remote Sensing Applied in Atmosphere (3rd Edition))

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14 pages, 1814 KiB

Open AccessEditor’s ChoiceArticle

Atmospheric Photochemical Oxidation of 4-Nitroimidazole

by Nayan Kondapalli, Oliver Cernero, Aaron Welch and Aaron W. Harrison

Atmosphere 2025, 16(5), 624; https://doi.org/10.3390/atmos16050624 - 20 May 2025

Viewed by 415

Abstract

Nitro-functionalized heterocycles, such as nitroimidazoles, are significant environmental contaminants and have been identified as components of secondary organic aerosols (SOA) and biomass-burning organic aerosols (BBOA). Their strong absorption in the near-UV (300–400 nm) makes photochemistry a critical aspect of their atmospheric processing. This [...] Read more.

Nitro-functionalized heterocycles, such as nitroimidazoles, are significant environmental contaminants and have been identified as components of secondary organic aerosols (SOA) and biomass-burning organic aerosols (BBOA). Their strong absorption in the near-UV (300–400 nm) makes photochemistry a critical aspect of their atmospheric processing. This study investigates both the direct near-UV photochemistry and hydroxyl radical (OH) oxidation of 4-nitroimidazole (4-NI). The atmospheric photolysis rate of 4-NI in the near-UV (300–400 nm) was found to be J_4-NI = 4.3 × 10⁻⁵ (±0.8) s⁻¹, corresponding to an atmospheric lifetime of 391 (±77) min under bulk aqueous conditions simulating aqueous aerosols and cloud water. Electrospray ionization mass spectrometry (ESI-MS) analysis following irradiation indicated loss of the nitro group, while NO elimination was observed as a more minor channel in direct photolysis. In addition, the rate constant for the reaction of 4-NI with OH radicals, k_NI+OH, was determined to be 2.9 × 10⁹ (±0.6) M⁻¹s⁻¹. Following OH oxidation, ESI-MS results show the emergence of a dominant peak at m/z = 130 amu, consistent with hydroxylation of 4-NI. Computational results indicate that OH radical addition occurs with the lowest barrier at the C2 and C5 positions of 4-NI. The combined results from direct photolysis and OH oxidation experiments suggest that OH-mediated degradation is likely to dominate under aerosol-phase conditions, where OH radical concentrations are elevated, while direct photolysis is expected to be the primary loss mechanism in high-humidity environments and bulk cloud water. Full article

(This article belongs to the Special Issue Recent Advances in Photochemistry and Spectroscopy of Atmospheric Aerosols)

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12 pages, 959 KiB

Open AccessEditor’s ChoiceArticle

Using Chemical Transport Model and Climatology Data as Backgrounds for Aerosol Optical Depth Spatial–Temporal Optimal Interpolation

by Natallia Miatselskaya, Andrey Bril and Anatoly Chaikovsky

Atmosphere 2025, 16(5), 623; https://doi.org/10.3390/atmos16050623 - 20 May 2025

Viewed by 354

Abstract

A common approach to estimating the spatial–temporal distribution of atmospheric species properties is data assimilation. Data assimilation methods provide the best estimate of the required parameter by combining observations with appropriate prior information (background) that can include the model output, climatology data, or [...] Read more.

A common approach to estimating the spatial–temporal distribution of atmospheric species properties is data assimilation. Data assimilation methods provide the best estimate of the required parameter by combining observations with appropriate prior information (background) that can include the model output, climatology data, or some other first guess. One of the relatively simple and computationally cheap data assimilation methods is optimal interpolation (OI). It estimates a value of interest through a weighted linear combination of observational data and background that is defined only once for the whole time interval of interest. Spatial–temporal OI (STOI) utilizes both spatial and temporal observational error covariance and background error covariance. This allows for filling in not only spatial, but also temporal gaps in observations. We applied STOI to daily mean aerosol optical depth (AOD) observations obtained at the European AERONET (Aerosol Robotic Network) sites with the use of the GEOS-Chem chemical transport model simulations and the AOD climatology data as backgrounds. We found that mean square errors in the estimate when using modeled data are comparable with those when using climatology data. Based on these results, we merged estimates obtained using modeled and climatology data according to their mean square errors. This allows for improving the AOD estimates in areas where observations are limited in space and time. Full article

(This article belongs to the Special Issue Data Analysis in Atmospheric Research)

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17 pages, 4685 KiB

Open AccessEditor’s ChoiceArticle

The Development and Application of a Three-Dimensional Corona Discharge Numerical Model Considering the Thunderstorm Electric Field Polarity Reversal Process

by Zhaoxia Wang, Bin Wu, Xiufeng Guo, Nian Zhao, He Zhang, Yubin Zhao and Yuhang Zheng

Atmosphere 2025, 16(5), 612; https://doi.org/10.3390/atmos16050612 - 17 May 2025

Viewed by 322

Abstract

The study of the ground tip corona discharge is an important part of the lightning strike mechanism and lightning warning research. Because the characteristics of the corona charge distribution are difficult to observe directly, simulation research is indispensable. However, most of the previous [...] Read more.

The study of the ground tip corona discharge is an important part of the lightning strike mechanism and lightning warning research. Because the characteristics of the corona charge distribution are difficult to observe directly, simulation research is indispensable. However, most of the previous models have been unipolar models, which cannot reflect the characteristics of the tip corona discharge under electric field reversal during real thunderstorms. Therefore, the development of three-dimensional positive and negative corona discharge models is of great significance. In this study, a three-dimensional corona discharge numerical model considering the polarity reversal process of the electric field was developed with or without a wind field and simulated the tip corona discharge characteristics under this reversal. The reliability of the model was verified by comparing the observed results. Compared with the unipolar corona discharge model, this model could effectively evaluate the impact of the first half-cycle corona discharge on the second half-cycle opposite-polarity corona discharge and invert the spatial separation distribution characteristics of different polar corona charges released in both cycles under the influence of wind and the spatial electric field distribution characteristics generated by the corresponding corona charges. Comparing unipolar corona discharges under the same wave pattern and amplitude of the background electric field, it was assumed that the unipolar corona discharge occurred in the half cycle after the polarity reversal of an electric field, and there was also an opposite-polarity corona discharge process before it. Due to the influence of the first half cycle, the background electric field required for a corona discharge was smaller, and the corona current was generated earlier, but the end time was equivalent. At the same time, due to the neutralization effect of positive and negative corona charges, the peak value of the total corona charge in the second half cycle was significantly smaller than that of the unipolar model. At different building heights, the peak difference in the corona current and the peak difference in the corona charge between the two models increased linearly with an increase in height. It could be seen that this model had better simulation results and wider application value. Full article

(This article belongs to the Section Meteorology)

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19 pages, 6942 KiB

Open AccessEditor’s ChoiceArticle

Analysis of Carbon Source/Sink Driving Factors Under Climate Change in the Inner Mongolia Grassland Ecosystem Through MGWR

by Ritu Wu, Zhimin Hong, Wala Du, Hong Ying, Rihan Wu, Yu Shan, Sainbuyan Bayarsaikhan and Dan Xiang

Atmosphere 2025, 16(5), 607; https://doi.org/10.3390/atmos16050607 - 16 May 2025

Viewed by 386

Abstract

Grassland ecosystems are essential components of the global ecosystem. They may efficiently reduce CO₂ concentrations in the atmosphere and play a vital role in mitigating climate change. The objectives of this study were to reveal the spatial distribution features of net primary [...] Read more.

Grassland ecosystems are essential components of the global ecosystem. They may efficiently reduce CO₂ concentrations in the atmosphere and play a vital role in mitigating climate change. The objectives of this study were to reveal the spatial distribution features of net primary production (NPP) and net ecosystem productivity (NEP) under climate change in the Inner Mongolia grassland ecosystem, China, and to devise effective management strategies for grassland ecosystems. Based on the multiscale geographically weighted regression (MGWR) model, this study investigated the spatial variation features of NPP and NEP along with their driving factors. The results showed the following: (1) The annual average NPP in the Inner Mongolia grassland ecosystem was 234.22

gC \cdot m^{- 2} \cdot a^{- 1}

, and the annual average NEP was 60.31

gC \cdot m^{- 2} \cdot a^{- 1}

from 2011 to 2022. Both measures showed a spatial pattern of high values in the northeast and low values in the southwest, as well as a temporal pattern of high values in summer and low values in winter. (2) The normalized difference vegetation index (NDVI) and solar radiation had promoting effects on NPP, where NDVI had the largest significant positive correlation area. In addition, precipitation and temperature on the influence of NPP were significantly negative with a larger area. (3) The area with a significant positive correlation of NDVI, solar radiation, and precipitation on NEP was larger than that with a significant negative correlation, while the area with significant negative correlation of temperature was larger. This study used the MGWR model to explore the relationship between NPP, NEP, and multiple factors. The results showed regional variation in NPP and NEP under the combined effect of various drivers. This contributes to a better understanding of carbon sinks under climate change in the Inner Mongolia grassland ecosystem. Full article

(This article belongs to the Special Issue Response of Vegetation to Climatic and Anthropogenic Drivers in the Plateau)

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31 pages, 7090 KiB

Open AccessEditor’s ChoiceArticle

Analysis of the Integrated Signal Design for Near-Space Communication, Navigation, and TT&C Based on K/Ka Frequency Bands

by Lvyang Ye, Shaojun Cao, Zhifei Gu, Deng Pan, Binhu Chen, Xuqian Wu, Kun Shen and Yangdong Yan

Atmosphere 2025, 16(5), 586; https://doi.org/10.3390/atmos16050586 - 13 May 2025

Viewed by 668

Abstract

With its unique environment and strategic value, the near space (NS) has become the focus of global scientific and technological, military, and commercial fields. Aiming at the problem of communication interruption when the aircraft re-enters the atmosphere, to ensure the needs of communication, [...] Read more.

With its unique environment and strategic value, the near space (NS) has become the focus of global scientific and technological, military, and commercial fields. Aiming at the problem of communication interruption when the aircraft re-enters the atmosphere, to ensure the needs of communication, navigation, and telemetry, tracking, and command (TT&C), this paper proposes an overall integration of communication, navigation, and TT&C (ICNT) signals scheme based on the K/Ka frequency band. Firstly, the K/Ka frequency band is selected according to the ITU frequency division, high-speed communication requirements, advantages of space-based over-the-horizon relay, overcoming the blackout problem, and the development trend of high frequencies. Secondly, the influence of the physical characteristics of the NS on ICNT is analyzed through simulation. The results show that when the K/Ka signal is transmitted in the NS, the path loss changes significantly with the elevation angle. The bottom layer loss at an elevation angle of 90° is between 143.5 and 150.5 dB, and the top layer loss is between 157.5 and 164.4 dB; the maximum attenuation of the bottom layer and the top layer at an elevation angle of 0° is close to 180 dB and 187 dB, respectively. In terms of rainfall attenuation, when a 30 GHz signal passes through a 100 km rain area under moderate rain conditions, the horizontal and vertical polarization losses reach 225 dB and 185 dB, respectively, and the rainfall attenuation increases with the increase in frequency. For gas absorption, the loss of water vapor is higher than that of oxygen molecules; when a 30 GHz signal is transmitted for 100 km, the loss of water vapor is 17 dB, while that of oxygen is 2 dB. The loss of clouds and fog is relatively small, less than 1 dB. Increasing the frequency and the antenna elevation angle can reduce the atmospheric scintillation. In addition, factors such as the plasma sheath and multipath also affect the signal propagation. In terms of modulation technology, the constant envelope signal shows an advantage in spectral efficiency; the new integrated signal obtained by integrating communication, navigation, and TT&C signals into a single K/Ka frequency point has excellent characteristics in the simulation of power spectral density (PSD) and autocorrelation function (ACF), verifying the feasibility of the scheme. The proposed ICNT scheme is expected to provide an innovative solution example for the communication, navigation, and TT&C requirements of NS vehicles during the re-entry phase. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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18 pages, 3673 KiB

Open AccessEditor’s ChoiceArticle

Effects of Smoke on Surface Observations, Turbulence, and Proposed Subcritical Aerosol-Moisture Feedback (SAMF) During the 8 April 2024 Solar Eclipse in Columbus, GA, USA

by Stephen M. Jessup and Britney Blaire Enfinger

Atmosphere 2025, 16(5), 578; https://doi.org/10.3390/atmos16050578 - 12 May 2025

Viewed by 991

Abstract

Very rarely, the atmosphere produces a natural experiment that, if captured, has the potential to lend insight into the fundamentals of atmospheric behavior. During the North American solar eclipse on 8 April 2024, a prescribed fire on the grounds of Fort Benning produced [...] Read more.

Very rarely, the atmosphere produces a natural experiment that, if captured, has the potential to lend insight into the fundamentals of atmospheric behavior. During the North American solar eclipse on 8 April 2024, a prescribed fire on the grounds of Fort Benning produced a smoky haze in Columbus, Georgia, USA. This haze covered the Columbus State University main campus and the nearby Columbus Airport (KCSG) leading up to and during the peak of the eclipse. Automated Surface Observing Station (ASOS) and Georgia Weather Network observations were examined for the event. At the time of temperature minimum, the temperature depression at KCSG was 0.5 °C greater than at nearby ASOS stations. An “eclipse wind” was observed at KCSG but not at the nearby ASOS stations. Based on observations of steady-state air and dewpoint temperatures, together with rapid fluctuations in visibility, we propose the Subcritical Aerosol-Moisture Feedback (SAMF) mechanism, in which subtle feedbacks among particle growth, relative humidity, and scattering of radiation by aerosol-laden air may maintain steady-state thermodynamic conditions. This case study offers a unique opportunity to examine aerosol behavior under transient radiative forcing, suggesting insights into how a smoky environment enhances thermal buffering and stabilizes the boundary-layer response under rare conditions. Full article

(This article belongs to the Section Meteorology)

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36 pages, 12610 KiB

Open AccessEditor’s ChoiceArticle

Analyzing the Mediterranean Tropical-like Cyclone Ianos Using the Moist Static Energy Budget

by Miriam Saraceni, Lorenzo Silvestri and Paolina Bongioannini Cerlini

Atmosphere 2025, 16(5), 562; https://doi.org/10.3390/atmos16050562 - 8 May 2025

Viewed by 352

Abstract

This paper presents a detailed analysis of the energy dynamics of the Mediterranean tropical-like cyclone, Medicane Ianos, by using a moist static energy (MSE) budget framework. Medicanes are hybrid cyclonic systems that share characteristics of both extratropical and tropical cyclones, making their classification [...] Read more.

This paper presents a detailed analysis of the energy dynamics of the Mediterranean tropical-like cyclone, Medicane Ianos, by using a moist static energy (MSE) budget framework. Medicanes are hybrid cyclonic systems that share characteristics of both extratropical and tropical cyclones, making their classification and prediction challenging. Using high-resolution ERA5 reanalysis data, we analyzed the life cycle of Ianos, which is one of the strongest recorded medicanes, employing the vertically integrated MSE spatial variance budget to quantify the contributions of different energy sources to the cyclone’s development. The chosen study area was approximately 2500² km², covering the entire track of the cyclone. The budget was calculated after tracking Ianos and applying Hart phase space analysis to assess the cyclone phases. The results show that the MSE budget can reveal that the cyclone development was driven by a delicate balance between convection and dynamical factors. The interplay between vertical and horizontal advection, in particular the upward transport of moist air and the lateral inflow of warm, moist air and cold, dry air, was a key mechanism driving the evolution of Ianos, followed by surface fluxes and radiative feedback. By analyzing what process contributes most to the increase in MSE variance, we concluded that Ianos can be assimilated in the tropical framework within a radius of 600 km around the cyclone center, but only during its intense phase. In this way, the budget can contribute as a diagnostic tool to the ongoing debate regarding medicanes classification. Full article

(This article belongs to the Section Meteorology)

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16 pages, 15852 KiB

Open AccessEditor’s ChoiceArticle

Evaluation and Mapping of Snow Characteristics Using Remote Sensing Data in Astore River Basin, Pakistan

by Ihsan Ullah Khan, Mudassar Iqbal, Zeshan Ali, Abu Bakar Arshed, Mo Wang and Rana Muhammad Adnan

Atmosphere 2025, 16(5), 550; https://doi.org/10.3390/atmos16050550 - 6 May 2025

Viewed by 485

Abstract

Being an agricultural country, Pakistan requires lots of water for irrigation. A major portion of its water resources is located in the upper indus basin (UIB). The snowmelt runoff generated from high-altitude areas of the UIB provides inflow into the Indus river system [...] Read more.

Being an agricultural country, Pakistan requires lots of water for irrigation. A major portion of its water resources is located in the upper indus basin (UIB). The snowmelt runoff generated from high-altitude areas of the UIB provides inflow into the Indus river system that boosts the water supply. Snow accumulation during the winter period in the highlands in the watershed(s) becomes a source of water inflow during the snow-melting period, which is described according to characteristics like snow depth, snow density, and snow water equivalent. Snowmelt water release (SWE) and snowmelt water depth (SD) maps are generated by tracing snow occurrence from MODIS-based images of the snow-cover area, evaluating the heating degree days (HDDs) from MODIS-derived images of the land surface temperature, computing the solar radiation, and then assimilating all the previous data in the form of the snowmelt model and ground measurements of the snowmelt water release (SWE). The results show that the average snow-cover area in the Astore river basin, in the upper indus basin, ranges from 94% in winter to 20% in summer. The maps reveal that the annual average values of the SWE range from 150 mm to 535 mm, and the SD values range from 600 mm to 2135 mm, for the snowmelt period (April–September) over the years 2010–2020. The areas linked with vegetation experience low SWE accumulation because of the low slopes in the elevated regions. The meteorological parameters and basin characteristics affect the SWE and can determine the SD values. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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25 pages, 20166 KiB

Open AccessEditor’s ChoiceArticle

Sensitivity Analysis and Performance Evaluation of the WRF Model in Forecasting an Extreme Rainfall Event in Itajubá, Southeast Brazil

by Denis William Garcia, Michelle Simões Reboita and Vanessa Silveira Barreto Carvalho

Atmosphere 2025, 16(5), 548; https://doi.org/10.3390/atmos16050548 - 5 May 2025

Cited by 1 | Viewed by 585

Abstract

On 27 February 2023, the municipality of Itajubá in southeastern Brazil experienced a short-duration yet high-intensity rainfall event, causing significant socio-economic impacts. Hence, this study evaluates the performance of the Weather Research and Forecasting (WRF) model in simulating this extreme event through a [...] Read more.

On 27 February 2023, the municipality of Itajubá in southeastern Brazil experienced a short-duration yet high-intensity rainfall event, causing significant socio-economic impacts. Hence, this study evaluates the performance of the Weather Research and Forecasting (WRF) model in simulating this extreme event through a set of sensitivity numerical experiments. The control simulation followed the operational configuration used daily by the Center for Weather and Climate Forecasting Studies of Minas Gerais (CEPreMG). Additional experiments tested the use of different microphysics schemes (WSM3, WSM6, WDM6), initial and boundary conditions (GFS, GDAS, ERA5), and surface datasets (sea surface temperature and soil moisture from ERA5 and GDAS). The model’s performance was evaluated by comparing the simulated variables with those from various datasets. We primarily focused on the representation of the spatial precipitation pattern, statistical metrics (bias, Pearson correlation, and Kling–Gupta Efficiency), and atmospheric instability indices (CAPE, K, and TT). The results showed that none of the simulations accurately captured the amount and spatial distribution of precipitation over the region, likely due to the complex topography and convective nature of the studied event. However, the WSM3 microphysics scheme and the use of ERA5 SST data provided slightly better representation of instability indices, although these configurations still underperformed in simulating the rainfall intensity. All simulations overestimated the instability indices compared to ERA5, although ERA5 itself may underestimate the convective environments. Despite some performance limitations, the sensitivity experiments provided valuable insights into the model’s behavior under different configurations for southeastern Brazil—particularly in a convective environment within mountainous terrain. However, further evaluation across multiple events is recommended. Full article

(This article belongs to the Section Meteorology)

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19 pages, 2139 KiB

Open AccessEditor’s ChoiceArticle

Analysis of VOC Emission Characteristics in the Petrochemical Industry and Study on Fenceline Monitoring Techniques

by Hyo Eun Lee, Seok J. Yoon and Jeong Hun Kim

Atmosphere 2025, 16(5), 543; https://doi.org/10.3390/atmos16050543 - 4 May 2025

Viewed by 478

Abstract

Volatile organic compounds (VOCs) contribute to air pollution and pose health risks. This study investigates VOC emissions from petroleum refining and petrochemical industries using passive and active fenceline monitoring techniques. The primary objective of this research is to compare the characteristics and detection [...] Read more.

Volatile organic compounds (VOCs) contribute to air pollution and pose health risks. This study investigates VOC emissions from petroleum refining and petrochemical industries using passive and active fenceline monitoring techniques. The primary objective of this research is to compare the characteristics and detection performance of passive and active sampling methods for VOC monitoring, particularly focusing on benzene and other major components, such as BTEX. A total of 87 VOC species were analyzed, with benzene, toluene, ethylbenzene, and xylene (BTEX) being dominant. Passive sampling detected benzene at an average concentration of 3.60 µg/m³, whereas active sampling recorded 1.33 µg/m³, showing up to 2.5 times higher values in passive sampling. In certain locations, benzene levels exceeded the EPA action level of 9 µg/m³, with a peak value of 18.37 µg/m³ at one sampling point. Meteorological conditions significantly influenced VOC concentrations, with stronger winds dispersing emissions more widely. This study provides crucial data for VOC emission control and regulatory policy development, emphasizing the need for continuous monitoring and targeted reduction strategies in industrial zones. 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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14 pages, 2180 KiB

Open AccessEditor’s ChoiceArticle

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 341

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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22 pages, 9592 KiB

Open AccessEditor’s ChoiceArticle

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 470

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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26 pages, 15535 KiB

Open AccessEditor’s ChoiceArticle

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 277

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

Open AccessEditor’s ChoiceArticle

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 488

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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16 pages, 5654 KiB

Open AccessEditor’s ChoiceArticle

Sizing Accuracy of Low-Cost Optical Particle Sensors Under Controlled Laboratory Conditions

by Prakash Gautam, Andrew Ramirez, Salix Bair, William Patrick Arnott, Judith C. Chow, John G. Watson, Hans Moosmüller and Xiaoliang Wang

Atmosphere 2025, 16(5), 502; https://doi.org/10.3390/atmos16050502 - 26 Apr 2025

Viewed by 621

Abstract

Low-cost particulate matter sensors have seen increased use for monitoring at personal and local levels due to their affordability, ease of operation, and high time resolution. However, the quality of data reported by these sensors can be questionable, and a thorough evaluation of [...] Read more.

Low-cost particulate matter sensors have seen increased use for monitoring at personal and local levels due to their affordability, ease of operation, and high time resolution. However, the quality of data reported by these sensors can be questionable, and a thorough evaluation of their performance is necessary. This study evaluated the particle sizing accuracy of several commonly used optical sensors, including the Alphasense optical particle counter (OPC), TSI DustTrak DRX aerosol monitor, Plantower PMS5003 sensor, and Sensirion SPS30 sensor, using laboratory-generated monodisperse particles. The OPC and DRX agreed partially with reference instruments and showed promise in detecting coarse-size particles. However, the PMS5003 and SPS30 did not correctly size fine and coarse particles. Furthermore, their reported mass distributions do not directly correspond to their number distribution. Despite these limitations, field measurements involving a dust storm period showed that the SPS30 correlated reasonably well with reference instruments for both PM_2.5 and PM₁₀, though the regression slopes differed significantly. These findings underscore the need for caution when interpreting data from low-cost optical sensors, particularly for coarse particles. Recommendations for improving the performance of these sensors are also provided. Full article

(This article belongs to the Section Aerosols)

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14 pages, 5256 KiB

Open AccessEditor’s ChoiceArticle

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 460

Abstract

Based on the hourly concentration data of PM_2.5, 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 PM_2.5, 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 PM_2.5, 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 PM_2.5, 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

Open AccessEditor’s ChoiceArticle

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 435

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

Open AccessEditor’s ChoiceArticle

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 889

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 (PM_2.5)—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

Open AccessEditor’s ChoiceArticle

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 435

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

Open AccessEditor’s ChoiceArticle

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 559

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 PM_2.5 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 PM_2.5 and 47% for PM₁₀ mass concentrations. Efficiency shows moss species’ maximum or optimal ability to absorb pollution PM_2.5 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 PM_2.5 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

Open AccessEditor’s ChoiceArticle

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 288

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, 6167 KiB

Open AccessEditor’s ChoiceArticle

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 414

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 PM_2.5, 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 PM_2.5 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 PM_2.5 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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15 pages, 1785 KiB

Open AccessEditor’s ChoiceArticle

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 499

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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18 pages, 7773 KiB

Open AccessEditor’s ChoiceArticle

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 354

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

Open AccessEditor’s ChoiceArticle

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 361

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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19 pages, 2732 KiB

Open AccessEditor’s ChoiceArticle

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 951

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, PM_2.5, 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, PM_2.5, 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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18 pages, 9863 KiB

Open AccessEditor’s ChoiceArticle

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 507

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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12 pages, 1210 KiB

Open AccessEditor’s ChoiceArticle

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 384

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

Open AccessEditor’s ChoiceArticle

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 474

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

Open AccessEditor’s ChoiceArticle

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

Cited by 1 | Viewed by 566

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

Open AccessEditor’s ChoiceArticle

Long-Term Trends in PM₁₀, PM_2.5, 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

Cited by 2 | Viewed by 868

Abstract

This study aimed to assess the long-term trends in PM₁₀, PM_2.5, 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, PM_2.5, 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 PM_2.5 levels varied between 100.7 ± 18.7 µg/m³ and 109.8 ± 21.3 µg/m³. A seasonal analysis showed the highest PM₁₀ and PM_2.5 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

Open AccessEditor’s ChoiceArticle

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 332

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 (A_M) reservoir, reflecting high surface temperatures and a lapse rate characteristic of a dry atmosphere, dominates other energy reservoirs. A_M is converted into the time-mean kinetic energy (K_M) and the time-variability available enthalpy (A_E) reservoirs, which are converted into a time-variability kinetic energy reservoir (K_E) through barotropic and baroclinic processes. A_E is the lowest energy reservoir, confirming smaller temperature variations in the tropics compared to higher latitudes. Kinetic energy reservoirs K_M and K_E 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 (A_E and K_E) and main terms acting upon them, are proportional to the rainfall activity, being higher (lower) during rainy (dry) years. It also reveals that, while C_A (conversion from A_M to A_E) and the generation term G_E feed wave’s development, the frictional term D_E counteracts the generation of K_E 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

Open AccessEditor’s ChoiceArticle

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 683

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

Open AccessEditor’s ChoiceReview

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

Cited by 1 | Viewed by 1093

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

Open AccessEditor’s ChoiceArticle

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 333

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

A_{h}

, horizontal reflectivity

Z_{h}

, differential reflectivity

Z_{d r}

, and specific differential phase

K_{d p}

) 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

A 1 : R (Z, K_{d p})

and

A 12 : R (Z_{d r}, K_{d p})

(among the bi-variable);

B 2 : R (Z_{h}, Z_{d r}, K_{d p})

and

B 3 : R (A_{h}, Z_{d r}, K_{d p})

(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

B 3 : R (A_{h}, Z_{d r}, K_{d p})

performs better than

B 2 : R (Z_{h}, Z_{d r}, K_{d p})

. Full article

(This article belongs to the Special Issue Applications of Meteorological Radars in the Atmosphere)

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23 pages, 8567 KiB

Open AccessEditor’s ChoiceArticle

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 425

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 θ_ITCZ from ERA5 are generally anti-correlated, and the correlation coefficients between AHT and θ_ITCZ from different methods are all significant. The multi-method mean northward shift of θ_ITCZ is 3.48 °PW⁻¹. Full article

(This article belongs to the Section Meteorology)

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