Atmosphere

26 pages, 5068 KB

Open AccessArticle

Machine Learning-Based Hydrological Drought Prediction Integrating Teleconnections and Hydrological Memory in a Semi-Arid Basin, Algeria

by Okan Mert Katipoğlu, Mohammed Achite, Veysi Kartal, Mehmet Ali Çelik and Kusum Pandey

Atmosphere 2026, 17(7), 670; https://doi.org/10.3390/atmos17070670 (registering DOI) - 4 Jul 2026

Abstract

Hydrological drought forecasting in semi-arid basins is challenging due to the combined influence of meteorological forcing, large-scale atmospheric teleconnections, and basin memory processes, which are rarely jointly analysed within a leakage-free predictive framework. This study addresses this gap by evaluating gradient-boosted trees and [...] Read more.

Hydrological drought forecasting in semi-arid basins is challenging due to the combined influence of meteorological forcing, large-scale atmospheric teleconnections, and basin memory processes, which are rarely jointly analysed within a leakage-free predictive framework. This study addresses this gap by evaluating gradient-boosted trees and neural forecasting models for one-month-ahead prediction of the Standardized Runoff Index (SRI) in two sub-basins of the Wadi Sahaouat Basin, Algeria. The models include gradient-boosted regression trees (GBRT), A-N-BEATS, A-N-HiTS, and TiDE, representing distinct forecasting architectures. Predictors consist of the Standardised Precipitation Index (SPI), seven teleconnection indices (NAO, AO, EAWR, SCAND, MEI, SOI, WeMO), and their one- to three-month lags. Two scenarios are tested: Scenario 1 uses SPI and teleconnection lags only, while Scenario 2 additionally includes lagged SRI values (SRI_lag1–3) to represent hydrological memory. A train-only Variance Inflation Factor (VIF > 10) procedure is applied to remove multicollinearity without data leakage. In Basin 1, SRI lags were excluded due to strong collinearity with SPI lags (r = 0.984), resulting in identical inputs for both scenarios. In Basin 2, SRI lags were retained to assess their predictive contribution. GBRT achieved the best overall performance across both basins and scenarios, with mean RMSE, NSE, and KGE values of 0.0682, 0.9907, and 0.8945, respectively. TiDE ranked second overall, with a mean RMSE of 0.1166, followed by A-N-HiTS in third place with a mean RMSE of 0.1203 and A-N-BEATS with the weakest overall performance, with a mean RMSE of 0.2159. These results indicate that gradient-boosted trees remain highly competitive with neural models for small monthly hydrological datasets and that the value of hydrological memory is basin-dependent and varies according to its independence from concurrent meteorological forcing. Full article

(This article belongs to the Special Issue Machine Learning for Hydrological Prediction and Water Management)

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26 pages, 47310 KB

Open AccessArticle

Evaluation of Precipitation and Temperature from Multiple Products and CMIP6 Simulations over the Qinghai–Tibet Plateau

by Wenhui Li, Tiexi Chen, Xin Chen, Jie Zhang, Shengzhen Wang, Yang Yang and Zhe Gu

Atmosphere 2026, 17(7), 669; https://doi.org/10.3390/atmos17070669 (registering DOI) - 4 Jul 2026

Abstract

Climate change is profoundly altering precipitation and temperature patterns across high-altitude regions worldwide. The Qinghai–Tibet Plateau (QTP), known as the “Third Pole” and the “Asian Water Tower,” is among the most climate-sensitive regions and plays a critical role in the Asian water cycle, [...] Read more.

Climate change is profoundly altering precipitation and temperature patterns across high-altitude regions worldwide. The Qinghai–Tibet Plateau (QTP), known as the “Third Pole” and the “Asian Water Tower,” is among the most climate-sensitive regions and plays a critical role in the Asian water cycle, cryospheric stability, and regional ecological security. However, the complex topography and diverse climate of the QTP result in substantial discrepancies among meteorological products over this region, highlighting the necessity of a comprehensive evaluation against in situ observational records. Using records from 85 stations (1960–2022), we evaluated four products: China’s 1 km monthly dataset (CN_1km), the Climatic Research Unit gridded Time Series (CRU TS), the fifth-generation European Centre for Medium-Range Weather Forecasts land reanalysis (ERA5-Land), and TerraClimate—selected for their long-term continuity, diverse product types, and widespread regional applications. Subsequently, we compared these products with Earth System Model (ESM) simulations from the NASA Earth Exchange Global Daily Downscaled Projections based on CMIP6 (NEX–GDDP–CMIP6). This evaluation was conducted using key statistical metrics, including the coefficient of determination (R²), root mean square error (RMSE), Kling–Gupta efficiency (KGE), and bias, together with spatially distributed long-term trend analysis using the Sen’s slope estimator and Mann–Kendall test. Station-based evaluation shows that temperature datasets generally outperform precipitation datasets, with monthly mean temperature yielding R² values of 0.85–0.94, RMSE values of 2.38–4.79 °C, and KGE values ranging from −0.04 to 0.86. Monthly precipitation R² values of 0.74–0.81, RMSE values of 20.60–36.12 mm, and KGE values of 0.42–0.86. For anomalies, temperature performs better (R² = 0.41–0.67; RMSE = 0.80–1.41 °C) than precipitation (R² = 0.28–0.44; RMSE = 16.87–20.73 mm). Overall, CN_1km and TerraClimate provide the most reliable station-based temperature estimates, while TerraClimate shows the most robust precipitation performance. All four datasets consistently indicate warming and wetting trends, with temperature rising at 0.21–0.24 °C decade⁻¹ and precipitation increasing at 4.5–5.8 mm decade⁻¹, featuring stronger warming in the west and greater precipitation increases in the northeast; however, the precipitation trend in ERA5-Land does not reach statistical significance. NEX–GDDP–CMIP6 simulations reproduce comparable warming and moistening signals (0.22–0.23 °C decade⁻¹ and 4.1–4.7 mm decade⁻¹), though their precipitation distribution differs markedly from the other datasets, with the discrepancy primarily reflected in a pronounced latitudinal gradient. These results provide a reference for the selection of climate-forcing datasets in hydrological, ecological, and cryospheric studies across the QTP. Full article

(This article belongs to the Special Issue The Qinghai-Tibet Plateau: Its Climate/Ecology and Its Impact on Global Climate/Ecology)

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14 pages, 8559 KB

Open AccessArticle

Opposing Hemispheric Responses of Eastern Pacific Marine Low Clouds to ENSO

by Ehsan Erfani

Atmosphere 2026, 17(7), 668; https://doi.org/10.3390/atmos17070668 (registering DOI) - 4 Jul 2026

Abstract

Marine low clouds (MLCs) strongly affect Earth’s radiation budget due to their extensive coverage and strong reflection of incoming solar radiation. Despite their important role in the Earth system, the extent and mechanisms of MLC response to climate oscillations are not well understood. [...] Read more.

Marine low clouds (MLCs) strongly affect Earth’s radiation budget due to their extensive coverage and strong reflection of incoming solar radiation. Despite their important role in the Earth system, the extent and mechanisms of MLC response to climate oscillations are not well understood. In this study, the effect of the El Niño–Southern Oscillation (ENSO) on cloud and meteorological properties across the Pacific Ocean is investigated by integrating various satellite observations and reanalysis datasets. The results reveal a pronounced hemispheric asymmetry in the response of subtropical MLCs to ENSO. During El Niño events, the Northeast Pacific exhibits reduced cloud cover and weaker shortwave radiative cooling, while an opposite response is observed over the Southeast Pacific, where cloudiness and radiative cooling are enhanced. These contrasting responses are linked to distinct ENSO-driven meteorological changes between the two hemispheres. Over the Northeast Pacific, El Niño conditions weaken inversion strength and the subtropical high, suppressing MLCs. In contrast, the Southeast Pacific experiences enhanced inversion strength and lower-tropospheric geopotential height during El Niño, which favor MLC development. It is suggested that hemispheric asymmetries in the climatological positions and ENSO-induced responses of the Pacific subtropical highs contribute to the opposite MLC responses between the two hemispheres. These findings highlight the importance of large-scale controls in shaping regional cloud responses to climate variability and provide insights for improving cloud representation in global climate models. Full article

(This article belongs to the Special Issue Advances in Aerosol–Cloud Interactions: From Microphysical Processes to Earth System Model Evaluation)

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14 pages, 14377 KB

Open AccessArticle

Interhemispheric Differences of Gravity Waves in the Northern and Southern Polar Middle Atmosphere Observed by the Aura Microwave Limb Sounder

by Klemens Hocke and Wenyue Wang

Atmosphere 2026, 17(7), 667; https://doi.org/10.3390/atmos17070667 - 3 Jul 2026

Abstract

The Aura Microwave Limb Sounder (Aura/MLS) measures temperature profiles with a horizontal spacing of about 170 km along its near polar orbit. We highpass-filtered the horizontal temperature fluctuations along the suborbital track in the middle atmosphere. The characteristics of inertia gravity waves with [...] Read more.

The Aura Microwave Limb Sounder (Aura/MLS) measures temperature profiles with a horizontal spacing of about 170 km along its near polar orbit. We highpass-filtered the horizontal temperature fluctuations along the suborbital track in the middle atmosphere. The characteristics of inertia gravity waves with horizontal wavelengths between 200 and 825 km are evaluated for the equatorial region (10

^{\circ}

S to 10

^{\circ}

N), northern polar region (70

^{\circ}

N to 82

^{\circ}

N), and southern polar region (70

^{\circ}

S to 82

^{\circ}

S) over the time interval from August 2004 to December 2021. A modulation of gravity wave activity by quasi-biennial oscillations is present in the equatorial stratosphere but not in the equatorial mesosphere. The gravity wave activity in the southern polar mesosphere is stronger by a factor of up to 2 than in the northern polar mesosphere. The seasonal variation in the vertical structure of gravity wave activity shows strong interhemispheric differences. There are double layers of enhanced gravity wave activity in the upper mesosphere over Antarctica in the summer and the winter, while the northern polar region does not show a double layer structure of gravity wave activity. In the northern polar region, upper mesospheric gravity wave activity is decreased after the onset of major sudden stratospheric warmings. Full article

(This article belongs to the Section Upper Atmosphere)

27 pages, 10326 KB

Open AccessArticle

Drainage Performance Grading and Spatial Vulnerability Assessment of Urban Underpasses: A Case Study of Hangzhou

by Shaojie Lei, Yihan Lou, Yating Zhou, Yuzhou Zhang, Luoyang Wang and Tangao Hu

Atmosphere 2026, 17(7), 666; https://doi.org/10.3390/atmos17070666 - 2 Jul 2026

Abstract

Due to the rapid acceleration of urbanisation and the increasing occurrence of extreme rainfall events, underpasses have become critical hotspots of urban flooding vulnerability. In this study, we investigated 36 underpasses in Hangzhou using the Urban Flood Inundation Model (UFIM) to systematically evaluate [...] Read more.

Due to the rapid acceleration of urbanisation and the increasing occurrence of extreme rainfall events, underpasses have become critical hotspots of urban flooding vulnerability. In this study, we investigated 36 underpasses in Hangzhou using the Urban Flood Inundation Model (UFIM) to systematically evaluate their drainage performance. A high-resolution hydraulic simulation framework was developed by integrating terrain data, drainage pipe networks, pumping stations, and land-use information. Based on the maximum tolerable hourly rainfall derived from multi-scenario simulations, the facilities were divided into high-, medium-, and low-vulnerability groups. Our quantitative and spatial analyses reveal a pronounced core–periphery disparity: 41.7% of the underpasses were highly vulnerable (drainage threshold ≈ 61.3 mm/h), exhibiting significant spatial agglomeration in the older urban core. In contrast, facilities in newly developed peripheral areas demonstrated better drainage performance (threshold up to 75.6 mm/h). Furthermore, the backwater effect from downstream rivers at flood stages significantly constrains pump efficiency by increasing the static head requirement. Based on these spatial vulnerabilities and thresholds, targeted infrastructure optimisation and spatial planning strategies are proposed, shifting the focus from uniform engineering upgrades to vulnerability-based drainage capacity enhancements. Full article

(This article belongs to the Special Issue Water Resource Challenges and Sustainable Management Solutions Under the Interaction of Climate Change and Human Activities)

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23 pages, 5820 KB

Open AccessArticle

Urbanization-Induced Changes in Multi-Type Extreme High-Temperature Events in Zhejiang Province, 1980–2019

by Zihan Gui, Heshuai Qi, Tianyu Jia, Fei Su and Caiming Chen

Atmosphere 2026, 17(7), 665; https://doi.org/10.3390/atmos17070665 - 1 Jul 2026

Abstract

Global warming has increased the frequency and intensity of extreme high-temperature events, with evolution patterns differing substantially under various temperature–humidity combinations. This study used observational data from 21 meteorological stations in Zhejiang Province (1980–2019) and applied a mutually exclusive classification framework based on [...] Read more.

Global warming has increased the frequency and intensity of extreme high-temperature events, with evolution patterns differing substantially under various temperature–humidity combinations. This study used observational data from 21 meteorological stations in Zhejiang Province (1980–2019) and applied a mutually exclusive classification framework based on dual thresholds of dry-bulb and wet-bulb temperatures to categorize extreme high-temperature events into dry-type (DHW), humid-type (HHW), and compound-type (CHW). The results show that DHW frequency, duration, and intensity all exhibited significant increasing trends, with frequency rising at 0.32/10a and intensity at 1.92 °C/10a. HHW occurred with low frequency and showed no significant trend across the study period. CHW intensity increased significantly at 2.85 °C/10a, while frequency and duration remained stable. Spatially, DHW concentrated in northern and central inland areas, whereas CHW dominated along the eastern coastal belt, reflecting the contrasting influences of land–sea thermal contrast and moisture availability. Urbanization showed significant positive correlations with all DHW indicators and negative correlations with HHW trends, indicating an amplifying effect on dry heat through surface warming and reduced evapotranspiration, and a suppressive effect on humid heat through reduced surface moisture availability. These findings demonstrate that the intensification of extreme heat in this region is dominated by dry-type events, and that urbanization plays a dual role in amplifying dry heat while suppressing humid heat, providing a scientific basis for differentiated heat risk management and climate-adaptive urban planning. Full article

(This article belongs to the Section Climatology)

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32 pages, 4063 KB

Open AccessArticle

Indoor Environmental Air Quality Assessment of University Workspaces in Sharjah, United Arab Emirates

by Sara Al Darras, Rami Elhadi, Maha Abu Mahfoud, Lucy Semerjian, Nada Jaradat and Khaled Abass

Atmosphere 2026, 17(7), 664; https://doi.org/10.3390/atmos17070664 - 1 Jul 2026

Abstract

This study investigated indoor environmental air quality (IEAQ) across university workspaces at a higher education institution in Sharjah, United Arab Emirates (UAE), assessing environmental conditions that may influence occupant health, the surrounding environment, and sustainability. Physical parameters (temperature, relative humidity, noise, and illuminance), [...] Read more.

This study investigated indoor environmental air quality (IEAQ) across university workspaces at a higher education institution in Sharjah, United Arab Emirates (UAE), assessing environmental conditions that may influence occupant health, the surrounding environment, and sustainability. Physical parameters (temperature, relative humidity, noise, and illuminance), chemical parameters (indoor gases and particulate matter), and biological contaminants (airborne bacteria and fungi) were measured in semi-occupied indoor environments with a total of 68 random samples collected and analyzed. Perceived heat discomfort and environmental variability were assessed using the Thom Discomfort Index (TDI), Humidex Index, ANOVA, Kruskal–Wallis, Mann–Whitney U, and one-sample t-tests. Average measurements of relative humidity, temperature, noise, and illuminance were 60.7%, 21.6 °C, 57.5 dB, and 440 lux, respectively. Average concentrations of PM_2.5, PM₁₀, CO, and CO₂ were 1223 ppm, 104 ppm, 1 ppm, and 623 ppm, respectively. Microbial contamination was generally insignificant across most investigated workspaces. While most measured parameters remained within recommended threshold limit values (TLVs), elevated levels of noise, illuminance, and particulate matter were observed in selected workspaces. These findings demonstrate that university indoor environments generally maintain acceptable air quality conditions; however, targeted interventions, including improved HVAC maintenance and indoor pollutant management, are required to enhance sustainable university indoor environments and optimize occupant comfort. Full article

(This article belongs to the Special Issue Indoor Air Quality and Health: Emerging Pollutants, Sources, and Impact)

1 pages, 126 KB

Open AccessRetraction

RETRACTED: Huang et al. The Application Research of FCN Algorithm in Different Severe Convection Short-Time Nowcasting Technology in China, Gansu Province. Atmosphere 2024, 15, 241

by Wubin Huang, Jing Fu, Xinxin Feng, Runxia Guo, Junxia Zhang and Yu Lei

Atmosphere 2026, 17(7), 663; https://doi.org/10.3390/atmos17070663 - 30 Jun 2026

Abstract

The journal retracts the article titled “The Application Research of FCN Algorithm in Different Severe Convection Short-Time Nowcasting Technology in China, Gansu Province” [...] Full article

(This article belongs to the Section Climatology)

26 pages, 7844 KB

Open AccessArticle

Evaluation of Active and Passive Brake Emission Mitigation Strategies in Real Driving Scenarios

by Alexander Hentschel, Miles Kunze, Patrick Habedank, Valentin Ivanov and Sebastian Gramstat

Atmosphere 2026, 17(7), 662; https://doi.org/10.3390/atmos17070662 - 30 Jun 2026

Abstract

Brake wear particles are an increasingly relevant source of traffic-related particulate emissions and are addressed by the recently introduced Euro 7 emission regulation. Airborne fractions of brake wear emissions, in particular, have been associated with adverse effects on human health and other organisms. [...] Read more.

Brake wear particles are an increasingly relevant source of traffic-related particulate emissions and are addressed by the recently introduced Euro 7 emission regulation. Airborne fractions of brake wear emissions, in particular, have been associated with adverse effects on human health and other organisms. Although several brake particle mitigation strategies have demonstrated promising results under controlled laboratory conditions, their effectiveness under variable open-road driving conditions remains insufficiently understood. This study therefore investigates the transfer of two test-bench-validated mitigation strategies to a fully instrumented passenger vehicle capable of measuring brake particle number (PN) and particulate mass (PM) emissions. The first strategy is a passive approach based on a modified brake pad–disc material pairing, while the second is an active filtration system that extracts particle-laden air directly from the brake friction zone. Both approaches were evaluated during two open-road driving cycles: a real driving emissions (RDE)-compliant cycle and a more dynamic cycle characterized by higher brake stress. Airborne particle emissions were measured over a size range from 300 nm to 10 µm. During the RDE-compliant cycle, the passive approach reduced PN and PM emissions by 44% and 94%, respectively, compared with the reference brake system. Under the higher thermal and mechanical loads of the dynamic cycle, the reductions decreased to 10% for PN and 64% for PM. The active filtration system achieved an increase in PN of 4% in RDE conditions and 11% under high-severity driving. Nevertheless, PM emissions were reduced by 23–97%, depending on its operating mode of the filtration system and the associated airflow and energy demand. For high-severity driving, the PM emissions have been reduced by 40% compared to the reference braking system. These results show that both mitigation approaches hold the potential to reduce brake particle emissions under open-road conditions, although their effectiveness depends strongly on brake load and system operation. The study extends previous laboratory-based investigations by directly comparing passive and active mitigation strategies on the same vehicle under real-world driving conditions. Full article

(This article belongs to the Special Issue Brake Wear Particle Emissions: Formation, Transport, Sampling and Prevention)

20 pages, 2770 KB

Open AccessArticle

Dynamics of Vertical Distribution of Soil Organic Carbon in Black Soil Profile of Northeast China in Response to Changes in Land Cover and Land Use

by Li Zhang, Fangming Zeng, Gang Wang, Jianjun Fan, Ting Liu, Qin Tan, Tao Zhan and Lei Tong

Atmosphere 2026, 17(7), 661; https://doi.org/10.3390/atmos17070661 - 30 Jun 2026

Abstract

Anthropogenic land-use change influences soil organic carbon (SOC) dynamics by altering both biotic and abiotic soil factors. The carbon stable isotope ratio of SOC (δ¹³C) indicates the vegetation sources of organic carbon and legacy effects of historical land use, providing important [...] Read more.

Anthropogenic land-use change influences soil organic carbon (SOC) dynamics by altering both biotic and abiotic soil factors. The carbon stable isotope ratio of SOC (δ¹³C) indicates the vegetation sources of organic carbon and legacy effects of historical land use, providing important information for carbon dynamics. However, the mechanisms driving SOC dynamics in deep soils (>100 cm) under different land cover and land-use types remain poorly understood. Here, we analyzed the SOC content and δ¹³C in thick soil profiles (a thickness of 160 cm or 200 cm) under different land cover/land-use types in the typical black soil region of the Songnen Plain, Northeast China. The results showed that the average SOC content at 0–30 cm depth in natural forest land (38.87 g kg⁻¹) was higher than that in the forest land converted to cultivated land (31.66 g kg⁻¹), artificial forest land (22.63 g kg⁻¹), and perennial cultivated land (18.16 g kg⁻¹). Similarly, the average SOC content below 100 cm depth was higher in natural forest land (7.99 g kg⁻¹) than in artificial forest land (6.90 g kg⁻¹), the conversion of natural forest to cropland (6.59 g kg⁻¹), and perennial cultivated land (4.39 g kg⁻¹). Notably, significant positive correlations between δ¹³C and SOC were observed in both natural forest land and perennial cultivated land, presenting the synergistic effects on SOC probably influenced by carbon input, microbial communities, and environmental conditions. Further investigation revealed that soil moisture content and pH significantly influenced SOC content, probably by regulating organic matter decomposition rates. The natural forest land with high moisture content and low pH conditions created favorable environments for carbon preservation, whereas long-term cultivated cropland with low moisture content and high pH conditions accelerated carbon mineralization processes. These results indicate that land cover and land-use change not only significantly alter surface SOC content but also drive deep soil carbon cycling dynamics by regulating soil moisture content, pH and δ¹³C values. This study elucidates the intrinsic relationships between SOC content, δ¹³C, pH, and moisture content under land-use change, providing scientific support for land use-aware carbon management strategies in black soil regions. Full article

(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)

27 pages, 19580 KB

Open AccessArticle

FY-4B Satellite-Derived Cloud-Parameter Responses to Localized Short-Duration Heavy Rainfall over Complex Terrain in Sichuan

by Yanyang Zhang, Ping Zhu and Dan Lin

Atmosphere 2026, 17(7), 660; https://doi.org/10.3390/atmos17070660 - 30 Jun 2026

Abstract

This study investigated short-duration heavy-rainfall events in Sichuan during 2023–2025. A 35 km × 35 km cloud window centered on heavy-rainfall stations was constructed. Multiple cloud parameters in the window were statistically analyzed to examine their responses to heavy rainfall under different rainfall-intensity [...] Read more.

This study investigated short-duration heavy-rainfall events in Sichuan during 2023–2025. A 35 km × 35 km cloud window centered on heavy-rainfall stations was constructed. Multiple cloud parameters in the window were statistically analyzed to examine their responses to heavy rainfall under different rainfall-intensity classes. Representative cases were also examined. The results showed that: (1) Eight major cloud parameters, including minimum cloud-top brightness temperature and deep convection index, showed clear responses to heavy rainfall in both rainfall-intensity classes. (2) Heavy-rainfall locations were mainly found in large-gradient zones near the edges of low cloud-top brightness temperature regions (<220 K) and high cloud-top height regions (>12 km). Cloud-parameter extrema generally appeared before the end of peak rainfall. Samples with rainfall intensity > 50 mm·h⁻¹ were mainly associated with ice-phase cold cloud-tops. These cloud-tops had brightness temperatures below 200 K, heights above 15 km, and pressures below 100 hPa, indicating stronger convective activity. In contrast, the 20–50 mm·h⁻¹ samples showed relatively weaker convective activity. (3) When cloud-top brightness temperature < 220 K, deep convection index ≥ 40, cloud-top height ≥ 15 km, DTB13 ≤ −1 K, and cloud-top pressure ≤ 130 hPa occurred simultaneously or successively, the cloud window indicated potential for short-duration heavy rainfall. Full article

(This article belongs to the Section Meteorology)

15 pages, 8795 KB

Open AccessArticle

Spatiotemporal Analysis and Deep Learning-Based Prediction of Air Pollution in China, 2015–2024

by Kai Tan, Qianjun Ren, Yiting Huo, Lu Ran, Xiaofang Xu, Li Cao, Qianying Xiang, Huirong Duan, Shuhan Wang, Jisheng Nie and Xiujuan Yang

Atmosphere 2026, 17(7), 659; https://doi.org/10.3390/atmos17070659 - 30 Jun 2026

Abstract

Air quality in China has markedly improved over the past decade, yet pollution levels remain high and continue to threaten public health. This study analyzed the spatiotemporal variations in six air pollutants (PM_2.5, PM₁₀, SO₂, NO₂ [...] Read more.

Air quality in China has markedly improved over the past decade, yet pollution levels remain high and continue to threaten public health. This study analyzed the spatiotemporal variations in six air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, O₃, CO) across seven regions in China (2015–2024) using Kriging interpolation. The performance of Recurrent Neural Network (RNN), Long Short-term Memory (LSTM), and Convolutional Neural Network-Long Short-term Memory (CNN-LSTM) models was assessed using the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Coefficient of Determination (R²) metrics. Results showed that all pollutants exhibited overall declining trends, with SO₂ depicting the largest reduction (69.53%), while O₃ displayed intermittent increases from 2017 to 2024. North China recorded both the highest concentrations and the greatest reductions in PM_2.5, SO₂, and CO, whereas Southwest and South China maintained the lowest overall levels. Among the predictive models, LSTM achieved the highest overall accuracy (mean RMSE = 1.802, mean MAE = 0.915, R² > 0.99). These findings provide a comprehensive depiction of China’s air pollution evolution and highlight the potential of deep learning for region-specific air quality prediction and policy design. The results offer a quantitative foundation for optimizing differentiated control strategies and advancing precision air quality management. Full article

(This article belongs to the Section Air Quality)

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14 pages, 763 KB

Open AccessArticle

Indoor Radon in School Buildings in Northern Portugal: Insights from Active and Passive Monitoring

by Maria de Lurdes Dinis and Ana Sofia Silva

Atmosphere 2026, 17(7), 658; https://doi.org/10.3390/atmos17070658 - 30 Jun 2026

Abstract

Indoor radon is a key indoor air pollutant and a major contributor to population exposure to natural ionizing radiation, with relevance in school buildings where children and staff spend extended periods indoors. This study investigated indoor radon concentrations in two public schools located [...] Read more.

Indoor radon is a key indoor air pollutant and a major contributor to population exposure to natural ionizing radiation, with relevance in school buildings where children and staff spend extended periods indoors. This study investigated indoor radon concentrations in two public schools located in a radon-prone area of northern Portugal using a combined short- and long-term monitoring strategy. In the first phase, active RadonEye detectors were deployed for continuous winter measurements in four ground-floor rooms across two schools, with three rooms located in School S1 and one in School S2, providing hourly data to characterize temporal variability. In the second phase, CR-39 passive detectors were installed in the same spaces to obtain integrated long-term concentrations. Active monitoring revealed pronounced spatial and temporal variability, with mean concentrations ranging from 140 to 228 Bq/m³ and peak values reaching 586 Bq/m³. Radon levels generally declined during occupied periods and increased at night and on weekends, indicating the importance of ventilation and occupancy patterns in shaping indoor radon dynamics. Passive measurements ranged from 290 to 300 Bq/m³ in school S1 and from 84 Bq/m³ to 300 Bq/m³ in school S2, confirming higher long-term concentrations in S1. Although most measurements remained below the reference level of 300 Bq/m³, several rooms approached or temporarily exceeded this threshold. These findings highlight the value of combining active and passive techniques to improve radon assessment in school environments and support targeted ventilation and mitigation strategies to reduce exposure and improve indoor air quality. Full article

(This article belongs to the Section Air Quality)

20 pages, 34125 KB

Open AccessArticle

Monitoring Characteristics and Environmental Field Analysis of Low-Level Wind Shear Induced by “Easterly Backflow” at Xining Airport

by Ziyi Xiao, Dongbei Xu, Yuqi Wang, Xuan Huang and Wenjie Zhou

Atmosphere 2026, 17(7), 657; https://doi.org/10.3390/atmos17070657 - 30 Jun 2026

Abstract

A significant low-level wind shear event that occurred at Xining Caojiabu Airport on 10 April 2019 was comprehensively analyzed. The analysis utilized data from the airport’s ground automatic weather observation system (AWOS), lidar detection data, ERA5 reanalysis data from the European Centre for [...] Read more.

A significant low-level wind shear event that occurred at Xining Caojiabu Airport on 10 April 2019 was comprehensively analyzed. The analysis utilized data from the airport’s ground automatic weather observation system (AWOS), lidar detection data, ERA5 reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF), and ETOPO2v2 topographic data from the National Oceanic and Atmospheric Administration (NOAA). The analysis focused on the evolution of meteorological elements during the wind shear, lidar characteristics, large-scale environmental features, and the main influencing systems. The results indicate that this was a typical “easterly backflow” low-level wind shear event, representing a special type of cold-frontal low-level wind shear, with the wind shear occurring in the prefrontal area as the cold front approached the airport. During the passage of the wind shear, the AWOS stations at Runways 29 and 11 sequentially recorded pressure increases and temperature decreases, reflecting the gradual intrusion of cold air from east to west into the airport. Lidar Plan Position Indicator (PPI), Range-Height Indicator (RHI), and Doppler Beam Swinging (DBS) modes revealed that the wind shear appeared as convergence between southeast and northwest winds, with an impact on the airport that moved from east to west and from bottom to top, belonging to a meso-γ-scale system. The evolution of the sea-level pressure field, pressure-change field, frontogenesis function, and temperature advection indicated that cold air first moved eastward along the Hexi Corridor and then poured back into the Huangshui River Valley through the topographic gap at the eastern end of the Qilian Mountains. The easterly wind converged with the westerly wind, and the topographic funneling effect strengthened the easterly backflow and promoted its westward advance, leading to the occurrence of low-level wind shear. The large-scale influencing systems of this event included a transverse trough over Mongolia at 500 hPa, an upper-level frontal zone, an upper-level jet stream, and a surface cold front. The favorable conditions for the formation of this “easterly backflow” low-level wind shear were the strengthening of baroclinicity in the upper-level frontal zone, intensified cold advection, momentum downward transport induced by the upper-level jet and ageostrophic secondary circulation, and the easterly backflow and wind speed enhancement caused by the special topography. Full article

(This article belongs to the Section Meteorology)

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14 pages, 3156 KB

Open AccessArticle

Quantitative Reconstruction of Beijing’s Climate over 380 Years Ago

by Haiming Liu and Haiyan Bi

Atmosphere 2026, 17(7), 656; https://doi.org/10.3390/atmos17070656 - 30 Jun 2026

Abstract

To address the scarcity of natural archives in historical climate reconstruction, this study utilized the late Ming Dynasty text Jiu Jing Yi Shi (Reminiscences of the Old Capital) as a primary data source to extract botanical and phenological information, aiming to quantitatively reconstruct [...] Read more.

To address the scarcity of natural archives in historical climate reconstruction, this study utilized the late Ming Dynasty text Jiu Jing Yi Shi (Reminiscences of the Old Capital) as a primary data source to extract botanical and phenological information, aiming to quantitatively reconstruct climate parameters for the Beijing region circa 1644 CE. Using botanical textual research, 11 out of 20 recorded plant names were identified to the species level, 2 to the genus level, and 7 were classified as non-native species. Breaking from the traditional reliance solely on woody plants, we innovatively incorporated three herbaceous species into the coexistence analysis framework to enhance the accuracy of climate reconstruction. By comprehensively comparing four climate indicators—mean annual temperature (MAT), mean temperature of the coldest month (MTCM), mean temperature of the warmest month (MTWM), and annual precipitation (AP)—across three critical nodes (1368 CE, 1644 CE, and the present), this research revealed a “decline-then-rise” trajectory in Beijing’s temperature over the past 600 years, alongside corresponding variations in precipitation patterns. Results indicated that the cooling event in the Beijing region between 1368 CE and 1644 CE was synchronous with global cooling trends during the same period and demonstrated a climatic transition from maritime to continental characteristics in the region. This work not only expands the application of historical literature in paleoclimatology but also provides critical scientific evidence for understanding centennial-scale climate evolution in the East Asian monsoon region and predicting future climate trends. Full article

(This article belongs to the Section Climatology)

20 pages, 3077 KB

Open AccessArticle

Preliminary Assessment of Frozen Ground Thermal Degradation in the Yangtze–Yellow River Source Regions and Its Hydrological Associations with the Western Sichuan Basins

by Xuewei Fang, Chen Cheng, Xin Lai and Shihua Lyu

Atmosphere 2026, 17(7), 655; https://doi.org/10.3390/atmos17070655 - 30 Jun 2026

Abstract

The Tibetan Plateau sustains major Asian rivers through extensive cryospheric resources. However, hydrological associations of frozen ground degradation on downstream water availability remain insufficiently quantified. This study presents a preliminary assessment of thermal dynamics of frozen ground in the Yangtze–Yellow River source regions [...] Read more.

The Tibetan Plateau sustains major Asian rivers through extensive cryospheric resources. However, hydrological associations of frozen ground degradation on downstream water availability remain insufficiently quantified. This study presents a preliminary assessment of thermal dynamics of frozen ground in the Yangtze–Yellow River source regions and their hydrological associations with the western Sichuan basins during 1961–2017. Using the near-surface ground freezing index (GFI) as a proxy indicator, we quantified contrasting streamflow responses between the Yangtze River source region (YaSR) and Yellow River source region (YeSR), and their connections with four major rivers in the western Sichuan basins. Results reveal divergent streamflow responses across four rivers, with predominantly positive anomalies despite widespread precipitation decline since the 2000s. As a permafrost-dominated basin, the YaSR exhibits enhanced streamflow generation, with contributions increasing from 6.63% to 31.31% as degradation intensifies. Conversely, the YeSR, mainly occupied by seasonally frozen ground, shows immediate streamflow attenuation that diminishes from 65.71% to 13.86% as degradation advances. The YaSR exhibits statistically significant positive associations with Jinsha and Yalong streamflows, while the YeSR develops significant statistical associations with Min River variability despite limited physical connectivity. These findings highlight the importance of frozen ground dynamics in regional water resource assessments under continued climate change. Full article

(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)

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16 pages, 2538 KB

Open AccessArticle

Comparison and Source Apportionment of Water-Soluble Ions and Inorganic Elements in Autumn–Winter PM_2.5 in Taizhou Using Two Monitoring Techniques

by Cheng Sun, Yan Xu, Ying Wu, Yuxiang Wang, Jun Zhu, Hui Mao and Chenghao Tan

Atmosphere 2026, 17(7), 654; https://doi.org/10.3390/atmos17070654 - 30 Jun 2026

Abstract

To evaluate the applicability of online monitoring for water-soluble ions and inorganic elements in atmospheric PM_2.5, this study conducted a comparative analysis using both online and manual monitoring data collected in Taizhou during autumn and winter (18 September 2023–6 January 2024). [...] Read more.

To evaluate the applicability of online monitoring for water-soluble ions and inorganic elements in atmospheric PM_2.5, this study conducted a comparative analysis using both online and manual monitoring data collected in Taizhou during autumn and winter (18 September 2023–6 January 2024). The Positive Matrix Factorization (PMF) model was employed for source apportionment. For water-soluble ions, online and manual results for Cl⁻, NO₃⁻, SO₄²⁻, NH₄⁺, and K⁺ showed good agreement (R² > 0.8), while Na⁺ exhibited moderate correlation and Ca²⁺/Mg²⁺ showed poor correlation. For inorganic elements, eight elements (K, Ca, Cr, Mn, Fe, Zn, Pb, Si) agreed well between methods, though online values were consistently lower than manual ones. Cu and Ni showed poor correlation. The PMF source apportionment results from online and manual monitoring data indicate that PM_2.5 in Taizhou during autumn and winter mainly originated from six sources: traffic (25.8%, 28.9%), secondary nitrate (18.6%, 20.9%), dust (16.1%, 14.2%), sea salt (15.8%, 11.5%), secondary (12.1%, 13.8%) and biomass burning (11.6%, 10.7%). Sensitivity analysis confirmed the robustness of PMF results to uncertainty assumptions. Overall, the results suggest that online monitoring data are generally applicable for PM_2.5 chemical characterization and source apportionment in Taizhou. Full article

(This article belongs to the Special Issue Atmospheric Pollution Dynamics in China)

22 pages, 2652 KB

Open AccessReview

Temperature and Precipitation Associations with NDVI on the Qinghai–Tibet Plateau: A Systematic Review and Multilevel Meta-Analysis

by Liqiong Li, Qingsong Du and Shuhong Wang

Atmosphere 2026, 17(7), 653; https://doi.org/10.3390/atmos17070653 - 30 Jun 2026

Abstract

Normalized Difference Vegetation Index (NDVI) dynamics on the Qinghai–Tibet Plateau are widely examined, yet published studies report spatially and methodologically heterogeneous relationships with temperature and precipitation. This study synthesized correlation-based evidence through a systematic review and multilevel meta-analysis. The Web of Science Core [...] Read more.

Normalized Difference Vegetation Index (NDVI) dynamics on the Qinghai–Tibet Plateau are widely examined, yet published studies report spatially and methodologically heterogeneous relationships with temperature and precipitation. This study synthesized correlation-based evidence through a systematic review and multilevel meta-analysis. The Web of Science Core Collection search identified 597 records: one duplicate was removed, 596 unique records were screened, and 107 articles underwent full-text assessment. The main synthesis included 84 effects from 11 studies. After CR2 robust variance correction, pooled correlations were 0.371 for temperature (95% CI: 0.049–0.623; p = 0.029) and 0.394 for precipitation (95% CI: 0.119–0.613; p = 0.0138), with no reliable difference between drivers (p = 0.526). Positive directions persisted under assumed within-study sampling correlations and conservative effective sample size assumptions. When all monthly scale effects were excluded, pooled estimates remained positive, but confidence intervals crossed zero, indicating reduced precision and dependence on temporal resolution. The findings therefore support positive average NDVI associations with both climatic drivers but not spatially or temporally uniform responses. Full article

(This article belongs to the Special Issue The Qinghai-Tibet Plateau: Its Climate/Ecology and Its Impact on Global Climate/Ecology)

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19 pages, 9875 KB

Open AccessArticle

Proposal for a Simplified Method to Calculate the Concentration of CO₂ in a Classroom Using CFD Simulation and Its Experimental Validation

by Dariel Gustavo Hernández-Montalvo, Abelardo Rodríguez-León, Guillermo Efren Ovando-Chacón, Enrique Cruz-Octaviano and Mario Díaz-González

Atmosphere 2026, 17(7), 652; https://doi.org/10.3390/atmos17070652 - 30 Jun 2026

Abstract

The present study addresses the problems of predicting the distribution of CO₂ in a classroom where limited ventilation may compromise air quality. Through Computational Fluid Dynamics (CFD), a detailed analysis of airflow, temperature, and CO₂ dispersion was carried out; however, due [...] Read more.

The present study addresses the problems of predicting the distribution of CO₂ in a classroom where limited ventilation may compromise air quality. Through Computational Fluid Dynamics (CFD), a detailed analysis of airflow, temperature, and CO₂ dispersion was carried out; however, due to its high computational cost, real-time applications are limited. Therefore, this work proposes a simplified CFD approach to model human breathing based on a constant airflow velocity and an average CO₂ concentration, preserving mass balance while reducing computational demand. Three mathematical breathing models (constant, complete, and sinusoidal) were formulated and compared through CFD simulation with the classroom model. Subsequently, a CO₂ detection module based on SCD40 sensors was developed for the experimental validation of the simplified model, recreating the simulation conditions in a real environment. The results show strong agreement between the simplified model and the complex models, as well as with experimental measurements, with relative errors between 0.05% and 10% at different monitoring points. The proposed model reduced calculation time by more than 98% compared to the sinusoidal model, without compromising accuracy. These results show that the simplified model is an efficient alternative for predicting CO₂ concentration, allowing its integration into real-time control systems. Full article

(This article belongs to the Section Air Quality and Health)

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