Atmosphere

24 pages, 2627 KB

Open AccessEditor’s ChoiceArticle

Investigation of Engine Exhaust Conversion and N₂O/NH₃ Generation on Pd-Based Catalyst

by Chongyao Wang, Xin Wang, Jianwei Tan, Chen Dong, Liangxiao Hou, Jianyong Feng and Yunshan Ge

Atmosphere 2025, 16(9), 1038; https://doi.org/10.3390/atmos16091038 - 31 Aug 2025

Viewed by 705

Abstract

Natural gas (NG) engine catalysts face unique challenges in emission control due to their distinct raw emission characteristics. This study investigates the exhaust conversion and by-product generation of a Palladium-based catalyst of an NG engine through small-sample catalyst experiments, mainly focusing on the [...] Read more.

Natural gas (NG) engine catalysts face unique challenges in emission control due to their distinct raw emission characteristics. This study investigates the exhaust conversion and by-product generation of a Palladium-based catalyst of an NG engine through small-sample catalyst experiments, mainly focusing on the effect of feed gas composition on the conversion efficiency and N₂O/NH₃ emissions. Results show that N₂O is generated via NO reduction by H₂ (80~275 °C) and CO (275~400 °C) in the temperature range of 80~400 °C. NH₃ generation occurs at 175~550 °C, mainly via NO reduction by H₂ (supplied from the water–gas shift (WGS) reaction) and CO below 425 °C and exclusively by H₂ (supplied from the steam reforming (SR) reaction) above 425 °C. An increase (0.9705~1.0176) in lambda enhances CO and CH₄ conversion while reducing N₂O and NH₃ emissions, but it inhibits NO conversion and promotes NO₂ formation. A lambda of 0.9941 achieves high conversion efficiency (≥90%) for CO, CH₄, and NO, with reduced N₂O and zero NH₃ emissions. An increase in H₂O (8~16%) accelerates the WGS and SR reactions, improving pollutant conversion. However, it aggravates N₂O and NH₃ emissions, with peak levels rising by 54% and 31%, respectively. Increased H₂ (500~1500 ppm) preferentially consumes NO and reversely shifts the equilibrium of the WGS and SR reactions, reducing CO and CH₄ conversion while improving NO conversion. And it promotes N₂O selectivity at high temperature and NH₃ selectivity at low temperature and peak emissions, with peak concentrations increasing by 58% and 15%, respectively. These findings reveal the by-product formation mechanism in the catalyst, providing valuable insights for the emission control of NG-fueled engines. Full article

(This article belongs to the Special Issue Traffic Related Emission (3rd Edition))

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18 pages, 3013 KB

Open AccessEditor’s ChoiceArticle

Spatial Variation of PM₁₀ and PM_2.5 in Residential Indoor Environments in Municipalities Across Mexico City

by Elizabeth Vega, Ann Wellens, Anil Namdeo, Diana Meza-Figueroa, Octavio Ornelas, Jane Entwistle and Lindsay Bramwell

Atmosphere 2025, 16(9), 1039; https://doi.org/10.3390/atmos16091039 - 31 Aug 2025

Cited by 1 | Viewed by 1126

Abstract

Despite significant progress in controlling outdoor air pollution in Mexico City over the past three decades, indoor air pollution remains largely unaddressed. This is particularly concerning because health authorities advise people to stay indoors when outdoor pollution exceeds safe limits, yet indoor concentrations [...] Read more.

Despite significant progress in controlling outdoor air pollution in Mexico City over the past three decades, indoor air pollution remains largely unaddressed. This is particularly concerning because health authorities advise people to stay indoors when outdoor pollution exceeds safe limits, yet indoor concentrations can be higher. Two optical particle counters were deployed simultaneously indoors and outdoors in 38 homes across all municipalities in Mexico City. The average indoor 24 h PM_2.5 concentration was 24.5 µg m⁻³, while PM₁₀ concentration averaged 78.6 µg m⁻³ compared to outdoor averages of 20.5 µg m⁻³ and 72.0 µg m⁻³. The PM_2.5/PM₁₀ ratio was 0.3 both indoors and outdoors. Only 20% of the homes exhibited maximum outdoor PM_2.5 concentrations 3.6 times higher than indoor; in 18%, indoor and outdoor levels were similar (0.8–1.2); and 60% of homes recorded indoor maxima up to nine times the outdoor peaks. Elevated indoor PM_2.5 was primarily linked with cooking and, to a lesser extent, cleaning activities. Peaks in PM_2.5 persisted for 4–8 h before returning to baseline. Ensuring adequate indoor ventilation is critical to maintain indoor air quality below outdoor levels and comply with WHO guidelines, highlighting the need for targeted strategies to reduce indoor exposure in urban homes. Full article

(This article belongs to the Section Air Quality)

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24 pages, 7129 KB

Open AccessEditor’s ChoiceArticle

Numerical Investigation of the Cooling Performance of Water Mist Spray Inside an Idealized 2D Street Canyon

by Hongjie Chen, Handong Meng and Yaxing Du

Atmosphere 2025, 16(9), 1036; https://doi.org/10.3390/atmos16091036 - 31 Aug 2025

Cited by 1 | Viewed by 773

Abstract

In response to the urban heat island challenge, various mitigation measures have been explored, with water spray systems emerging as a cost-effective and efficient solution for urban outdoor cooling. However, the influential factors of a water spray system on cooling efficiency have not [...] Read more.

In response to the urban heat island challenge, various mitigation measures have been explored, with water spray systems emerging as a cost-effective and efficient solution for urban outdoor cooling. However, the influential factors of a water spray system on cooling efficiency have not been fully understood, thus hindering the application of the water spray system. This study delves into the following two questions: (1) what is the cooling performance of a water mist spray in a hot and humid urban climate? (2) What are the effects of different influencing factors? To answer these two questions, the computational fluid dynamics (CFD) simulations are used to modelthe cooling process of water mist spray inside an ideal two-dimensional street canyon with an aspect ratio of 1. A sound validation for the water spray cooling was conducted prior to the following CFD simulations. Results show that for given values of the water flow rate (i.e., 9.0 L/min) and the spray nozzle height (i.e., 3 m), a maximum temperature reduction of about 4.6 °C can be achieved at pedestrian height. Raising the installation height is more effective in maintaining the cooling zone proportion than decreasing the water flow rate. The clockwise recirculation inside the street canyon disappears with the upward airflow weakened when the spray nozzle is installed in the middle of the street canyon. Full article

(This article belongs to the Section Biometeorology and Bioclimatology)

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28 pages, 10580 KB

Open AccessEditor’s ChoiceArticle

A Study of the Low-Ozone Episode over Scandinavia and Northwestern Russia in March 2025

by Pavel Vargin, Sergei Smyshlyaev, Vladimir Guryanov, Natalia Chubarova, Dmitry Ionov, Tatjana Bankova, Natalya Ivanova and Anna Solomatnikova

Atmosphere 2025, 16(9), 1033; https://doi.org/10.3390/atmos16091033 - 30 Aug 2025

Viewed by 926

Abstract

Following a very cold first half of the Arctic stratosphere winter of 2024–2025, the stratospheric polar vortex weakened from late February. The increase in the polar lower stratosphere temperature led to a decrease in the polar stratospheric cloud (PSC) type I (NAT) volume [...] Read more.

Following a very cold first half of the Arctic stratosphere winter of 2024–2025, the stratospheric polar vortex weakened from late February. The increase in the polar lower stratosphere temperature led to a decrease in the polar stratospheric cloud (PSC) type I (NAT) volume from ~80 million km³ to zero. The polar vortex weakening and temperature increase continued in early March, when major sudden stratospheric warming occurred. Although the polar cap total column ozone (TCO) significantly increased during this period, an ozone mini-hole formed over Scandinavia and northwestern Russia, with TCO values as low as 220–240 Dobson units, according to satellite observations and ground-based measurements over St. Petersburg and Moscow on 5–6 March 2025. Chemistry-transport model calculations using MERRA2 reanalysis data were performed to investigate the role of chemical ozone depletion and dynamical processes in the low TCO values in early March. Model experiments show that dynamical processes played a predominant role in the formation of low TCO values, but the role of chemical processes was not negligible. Associated with the TCO anomaly, the difference relative to the standard ozone level in the UV indices over Moscow, St. Petersburg and Helsinki reached up to 60–100%. Full article

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

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18 pages, 16048 KB

Open AccessEditor’s ChoiceArticle

Ionospheric Variability During the 10 October 2024 Geomagnetic Storm: A Regional Analysis Across Europe

by Sharad C. Tripathi, Haris Haralambous and Trisani Biswas

Atmosphere 2025, 16(9), 1029; https://doi.org/10.3390/atmos16091029 - 30 Aug 2025

Viewed by 1938

Abstract

This study examines the ionospheric response to the intense geomagnetic storm of 9–12 October 2024 over the European sector. Digisonde data from mid-latitude European stations and in situ electron density measurements from Swarm A and B satellites were used to analyze variations in [...] Read more.

This study examines the ionospheric response to the intense geomagnetic storm of 9–12 October 2024 over the European sector. Digisonde data from mid-latitude European stations and in situ electron density measurements from Swarm A and B satellites were used to analyze variations in key ionospheric characteristics, including the critical frequency (foF2), peak height (hmF2) and plasma drift velocities. Significant uplift of the F2 layer and a corresponding reduction in foF2 were observed across latitudes, primarily driven by prompt penetration electric fields (PPEFs) and storm-induced thermospheric winds. Horizontal and vertical ion drifts showed large asymmetries and reversals, with zonal drift velocities exceeding 1000 m/s at some stations. Swarm observations confirmed plasma density enhancements during the main phase and notable depletions during recovery, particularly after 1:00 UT on 11 October. The midlatitude ionospheric trough (MIT) intensified during the recovery phase, as can be seen from Swarm B. These variations were shaped by electrodynamic forcing, compositional changes and disturbance dynamo electric fields (DDEFs). The results emphasize the role of solar wind drivers, latitude-dependent electrodynamic coupling and thermospheric dynamics in mid-latitude ionospheric variability during geomagnetic storms. 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, 728 KB

Open AccessEditor’s ChoiceReview

Systematic Review of Prenatal Exposure to PM_2.5 and Its Chemical Components and Their Effects on Neurodevelopmental Outcomes in Neonates

by Gabriele Donzelli, Isabel Peraita-Costa, Nunzia Linzalone and María Morales-Suárez-Varela

Atmosphere 2025, 16(9), 1034; https://doi.org/10.3390/atmos16091034 - 30 Aug 2025

Viewed by 1451

Abstract

Particulate matter with a diameter less than 2.5 µm (PM_2.5) and its chemical constituents—including ammonium (NH₄⁺), sulfate (SO₄²⁻), nitrate (NO₃⁻), organic carbon (OC), soil dust, and black carbon (BC)—have been increasingly recognized [...] Read more.

Particulate matter with a diameter less than 2.5 µm (PM_2.5) and its chemical constituents—including ammonium (NH₄⁺), sulfate (SO₄²⁻), nitrate (NO₃⁻), organic carbon (OC), soil dust, and black carbon (BC)—have been increasingly recognized for their potential impact on fetal neurodevelopment. This systematic review aimed to synthesize current evidence on the relationship between prenatal exposure to PM_2.5 and its chemical components and neurodevelopmental outcomes in neonates, focusing on diagnoses such as autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). Following PRISMA 2020 guidelines, a comprehensive literature search was conducted on PubMed and Embase databases from April to July 2025. Twenty-five studies meeting inclusion criteria were analyzed, of which sixteen addressed PM_2.5 exposure generally, and nine assessed specific chemical constituents. The findings indicate that increased exposure to PM_2.5, particularly during the third trimester, is associated with a higher risk of ASD. Additionally, prenatal exposure may adversely affect early neurodevelopmental domains including motor skills, problem-solving, and social interactions. Certain PM_2.5 components, notably sulfate ions (SO₄²⁻), were identified as important contributors to neurological health outcomes. These results underscore the importance of reducing prenatal exposure to PM_2.5 and its harmful constituents to protect neurodevelopment. Full article

(This article belongs to the Special Issue Air Pollution: Health Risks and Mitigation Strategies)

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16 pages, 2154 KB

Open AccessEditor’s ChoiceArticle

Estimation of Sensible and Latent Heat Fluxes from Different Ecosystems Using the Daily-Scale Flux Variance Method

by Yanhong Xie, Jingzheng Xu, Yini Pu, Lei Huang, Mi Zhang, Wei Xiao and Xuhui Lee

Atmosphere 2025, 16(9), 1030; https://doi.org/10.3390/atmos16091030 - 30 Aug 2025

Viewed by 547

Abstract

A daily-scale flux variance (FV) method, which employs low-frequency air temperature measurements, was assessed against eddy covariance (EC) measurements of sensible and latent heat fluxes at four sites representing grassland and cropland ecosystems. The sensible heat flux was estimated using two daily-scale FV [...] Read more.

A daily-scale flux variance (FV) method, which employs low-frequency air temperature measurements, was assessed against eddy covariance (EC) measurements of sensible and latent heat fluxes at four sites representing grassland and cropland ecosystems. The sensible heat flux was estimated using two daily-scale FV approaches: M1 (separating daytime and nighttime data) and M2 (integrating daily data), both derived from conventional formulations. The latent heat flux was extracted as a residual of the energy balance closure with the FV-estimated sensible heat flux and additional measurements of net radiation and soil heat flux. The results showed that the FV method performed poorly in estimating sensible heat flux across all four sites, primarily due to the negative flux values from cropland sites. In contrast, latent heat flux estimation showed reasonable agreement with EC measurements. Notably, upscaling the FV method from a half-daily (M1) to a daily (M2) scale did not improve the accuracy of sensible and latent heat flux estimations for most sites. The best performance for latent heat flux was achieved with M1 at a cropland site (YF), yielding a slope of 0.98, determination coefficient of 0.88, and root mean square error of 13.13 W m⁻². Overall, the daily-scale FV method—requiring only low-frequency air temperature data from microclimate systems—offers a promising approach for evapotranspiration monitoring, particularly at basic meteorological stations lacking high-frequency instrumentations. Full article

(This article belongs to the Section Biometeorology and Bioclimatology)

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11 pages, 2829 KB

Open AccessEditor’s ChoiceArticle

Low-Cost, LED-Based Photoacoustic Spectrophone Using Hemispherical Acoustic Resonant Cavity for Measurement of Hydrocarbon Gases

by Gaoxuan Wang, Lingxiao Hou, Fangjun Li, Lihui Wang, Chao Fei, Xiaojian Hong and Sailing He

Atmosphere 2025, 16(9), 1012; https://doi.org/10.3390/atmos16091012 - 28 Aug 2025

Viewed by 610

Abstract

Spherical acoustic resonant cavities have been increasingly reported in photoacoustic spectroscopy due to their small volume and enhanced effective gas absorption path length. For further reducing the acoustic cavity volume and exploiting broadband LED as a light source, this paper reports a low-cost, [...] Read more.

Spherical acoustic resonant cavities have been increasingly reported in photoacoustic spectroscopy due to their small volume and enhanced effective gas absorption path length. For further reducing the acoustic cavity volume and exploiting broadband LED as a light source, this paper reports a low-cost, LED-based photoacoustic gas-sensing system using a hemispherical acoustic resonant (HAR) cavity with a radius of 15 mm and a volume of 7.07 mL. The placement of both the excitation light source and transducer, as important elements in photoacoustic spectroscopy, was systematically optimized for improving the generation efficient of photoacoustic signal. The frequency response of the HAR cavity was thoroughly characterized for exploring an optimal operation frequency of the light source. Through positional and frequency optimization, the developed low-cost, LED-based photoacoustic spectrophone realized highly sensitive measurements of hydrocarbon gases with measurement sensitivities of 111.6 ppm (3σ) for isobutane, 140.1 ppm (3σ) for propane, and 866.4 ppm (3σ) for ethylene at an integration time of 1 s. These results demonstrate the strong potential of low-cost, LED-HAR-based PA-sensing systems in the field of gas sensing for widespread deployment in distributed sensor networks and atmospheric monitoring platforms. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling (2nd Edition))

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12 pages, 402 KB

Open AccessEditor’s ChoiceArticle

Exploring Carbon Emission Peak and Reduction Strategies in China’s Industrial Sector: A Case Study of Wuxi City

by Xianhong Qin and Xiaoyan Xu

Atmosphere 2025, 16(9), 1010; https://doi.org/10.3390/atmos16091010 - 28 Aug 2025

Viewed by 718

Abstract

As the world’s largest manufacturing country, China’s industrial carbon emission reduction is crucial to achieving its “dual carbon” goals. This paper takes Wuxi, a national low-carbon pilot city in Jiangsu Province, as a case, using a bottom-up factor decomposition model to study industrial [...] Read more.

As the world’s largest manufacturing country, China’s industrial carbon emission reduction is crucial to achieving its “dual carbon” goals. This paper takes Wuxi, a national low-carbon pilot city in Jiangsu Province, as a case, using a bottom-up factor decomposition model to study industrial carbon peak prediction and sector-specific emission reduction strategies. Results show that under the usual-growth scenario (UG), Wuxi’s industrial emissions keep growing and will not peak before 2030, reaching 122.18 million tCO₂ that year. Under the emission-controlled scenario (EC), with industrial structure optimization and energy intensity control, emissions peak in 2026 at 100.55 million tCO₂, 17.7% lower than the baseline. The reinforced-mitigation scenario (RM), combining in-depth structural adjustment and technological upgrade, sees the peak in 2025 at 94.22 million tCO₂, a 22.9% reduction. It is necessary to implement differentiated emission reduction strategies, focusing on high-emission and low-carbon productivity industries such as electricity and heat production, and ferrous metal smelting and rolling. Through precise management and control, the overall emission reduction efficiency can be improved, providing a reference paradigm for the low-carbon transformation of similar industrial cities. Full article

(This article belongs to the Special Issue Transport GHG Emissions)

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24 pages, 4067 KB

Open AccessEditor’s ChoiceArticle

A Hyperspectral Method for Detection of the Three-Dimensional Spatial Distribution of Aerosol in Urban Areas for Emission Source Identification and Health Risk Assessment

by Shun Xia, Qihua Li, Jian Chen, Zhiguo Zhang and Qihou Hu

Atmosphere 2025, 16(9), 999; https://doi.org/10.3390/atmos16090999 - 24 Aug 2025

Viewed by 627

Abstract

Studying the vertical and horizontal distribution of particulate matter at the hectometer scale in the atmosphere is essential for understanding its sources, transportation, and transmission and its impact on human health. In this study, a method was developed based on hyperspectral instrumentation to [...] Read more.

Studying the vertical and horizontal distribution of particulate matter at the hectometer scale in the atmosphere is essential for understanding its sources, transportation, and transmission and its impact on human health. In this study, a method was developed based on hyperspectral instrumentation to obtain both vertical and horizontal distributions of aerosol extinction by employing multiple azimuth angles, selecting optimized elevation angles, and reducing the acquisition time of individual spectra. This method employed observations from different azimuth angles to represent particulate matter concentrations in various directions. The correlation coefficient between the hyperspectral observations and in-situ measurement was 0.627. Observations indicated that the aerosol extinction profile followed an exponential decay, with most aerosols confined below 1 km, implying a likely origin from local near-surface emissions. The horizontal distribution indicated that the northeastern urban areas and the eastern rural areas were the primary regions with high concentrations of particulate matter. The observational evidence suggests the presence of two potential emission sources within the study area. Moreover, health risk results indicated that even within the same town, differences of particulate matter concentration and population density could lead to varying health exposure risks. For instance, in the 200° and 210° directions, which represent adjacent urban areas less than 1 km apart, the number of PM_2.5-related illness cases in the 210° direction was 20.83% higher than that in the 200° direction. Full article

(This article belongs to the Special Issue Application of Emerging Methods in Aerosol Research)

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11 pages, 875 KB

Open AccessEditor’s ChoiceArticle

Evidence for a New Oxidation Mechanism for Sulfur Dioxide from Laboratory Measurements

by William R. Stockwell and Rosa M. Fitzgerald

Atmosphere 2025, 16(9), 1000; https://doi.org/10.3390/atmos16091000 - 24 Aug 2025

Viewed by 835

Abstract

The oxidization of sulfur dioxide (SO₂) occurs in the gas and liquid phase and this oxidation contributes to particulate matter and acid precipitation. The production of sulfate particles is significant because of their impact on climate, precipitation acidification, and human health. [...] Read more.

The oxidization of sulfur dioxide (SO₂) occurs in the gas and liquid phase and this oxidation contributes to particulate matter and acid precipitation. The production of sulfate particles is significant because of their impact on climate, precipitation acidification, and human health. In this paper, the focus is on the oxidation of SO₂ and on the possibility of unknown heterogeneous reactions that may occur on sulfate aerosol surfaces. These results are based on the reanalysis of a foundational set of SO₂ laboratory oxidation measurements. The experiments involved two sets of photochemical studies of nitrous acid (HONO), nitrogen oxides (NO_x = NO + NO₂), SO₂, carbon monoxide (CO), and water vapor (H₂O) mixtures made in molecular nitrogen (N₂) with traces of molecular oxygen or in synthetic air. The reanalysis strongly suggests that there are uncharacterized processes for the oxidation of SO₂ that are nearly three times faster than the known gas-phase reactions. The uncharacterized processes may involve sulfate aerosol surface reactions in the presence of nitrogen oxides. If these processes can be included in current atmospheric chemistry models, greater conversion rates of SO₂ to sulfate aerosol will be calculated and this may reduce modeling bias. Full article

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

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21 pages, 8381 KB

Open AccessEditor’s ChoiceArticle

Wind-Induced Water Transport and Circulation Structure in the Laptev Sea–East Siberian Sea

by Xiangyun Liu, Yanjun Wu and Xiaoyu Wang

Atmosphere 2025, 16(9), 1001; https://doi.org/10.3390/atmos16091001 - 24 Aug 2025

Viewed by 679

Abstract

Variability in the Laptev Sea–East Siberian Sea circulation system modulates freshwater circulation in the Arctic Ocean, yet details of these wind-driven mechanisms remain poorly understood. Based on in situ observations from the 2018 Sino-Russian joint Arctic expedition, this study investigates the modulatory influence [...] Read more.

Variability in the Laptev Sea–East Siberian Sea circulation system modulates freshwater circulation in the Arctic Ocean, yet details of these wind-driven mechanisms remain poorly understood. Based on in situ observations from the 2018 Sino-Russian joint Arctic expedition, this study investigates the modulatory influence of wind on circulation structures and freshwater transport in the study area and examines the long-term variation characteristics of this circulation and its inherent connection with the Arctic wind. In situ measurements confirm two freshwater transport pathways: a coastal-current route and a geostrophic slope-current route. As the Beaufort High moves toward the Canadian Basin, it shifts wind patterns from anticyclonic to cyclonic, which regulates the transport of shelf water by influencing the prevailing wind direction. Furthermore, our analysis identifies two main modes of long-term changes in summer surface circulation: the first mode characterizes the coastal-current architecture, while the second mode delineates slope-current configurations. Crucially, large-scale modes of the Arctic wind play an important role in regulating circulation. Its first mode corresponds to the summer anticyclonic circulation pattern of the Arctic Ocean Oscillation, which drives the eastward strengthening of the coastal current, while the third mode presents a mechanism similar to the Arctic Dipole, which promotes the development of the slope current by enhancing the convergence of the polar current and wind. This has led to the long-term strengthening of the slope current. Full article

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

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19 pages, 5122 KB

Open AccessEditor’s ChoiceReview

An Overview of the Holocene High Sea Level Around the South China Sea: Age, Height, and Mechanisms

by Lei Zhang, Tongyan Lü, Lei Xue, Weiming Mo, Chaoqun Wang, Xitao Zhao and Daogong Hu

Atmosphere 2025, 16(8), 993; https://doi.org/10.3390/atmos16080993 - 21 Aug 2025

Viewed by 1943

Abstract

Understanding Holocene high sea levels in the South China Sea (SCS) is critical for understanding climate change and assessing future sea-level rise risks. We provide a comprehensive review of the Holocene highstand in the SCS, focusing on its age, height, and mechanisms. Records [...] Read more.

Understanding Holocene high sea levels in the South China Sea (SCS) is critical for understanding climate change and assessing future sea-level rise risks. We provide a comprehensive review of the Holocene highstand in the SCS, focusing on its age, height, and mechanisms. Records reveal a wide range for this highstand: ages span 3480–7500 cal yr BP, while elevations range from −7.40 to 7.53 m relative to the present. Positive elevations dominate (80.5% of records), with the most frequent range being 2–3 m. Regionally averaged formation times suggest a broadly synchronous mid-Holocene high-sea-level event across the SCS, potentially reflecting a global background. The observed variability is attributed to the interplay of multiple factors: global processes like glacial meltwater input and seawater thermal expansion, particularly during the Holocene warm period, and regional neotectonic movements (uplift/subsidence), which are the primary cause of spatial differences in reconstructed elevations. Significant debate persists regarding precise timing, height, and dominant mechanisms due to limitations in data coverage, dating precision, and challenges in quantifying tectonic influences. Future research priorities include obtaining high-resolution data from stable marine sediments, employing diverse dating techniques and modern crustal deformation monitoring, quantifying tectonic impacts, developing regional sea-level models, and enhancing international collaboration to refine understanding and improve predictions of future sea-level rise impacts. Full article

(This article belongs to the Special Issue The Evolution of Climate and Environment in the Holocene)

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34 pages, 3632 KB

Open AccessEditor’s ChoiceReview

Systematic Review and Meta-Analysis of Urban Air Quality in the Arabian Peninsula

by Elisephane Irankunda, Monica Menendez, Basit Khan, Francesco Paparella and Olivier Pauluis

Atmosphere 2025, 16(8), 990; https://doi.org/10.3390/atmos16080990 - 20 Aug 2025

Viewed by 1650

Abstract

Air pollution is causing a global health, climate, and environmental crisis. Air quality (AQ) in hyper-arid regions, such as the Arabian Peninsula, remains under-explored, posing significant concerns for public health and the scientific community. Both long-term and short-term exposure to high pollutant levels, [...] Read more.

Air pollution is causing a global health, climate, and environmental crisis. Air quality (AQ) in hyper-arid regions, such as the Arabian Peninsula, remains under-explored, posing significant concerns for public health and the scientific community. Both long-term and short-term exposure to high pollutant levels, whether from anthropogenic or natural sources, can pose serious health risks. This paper offers a comprehensive review and meta-analysis of urban AQ literature published in the region over the past decade (2013–June 2025). We aim to provide guidance and highlight key directions for future research in the field. This paper examines key pollutants, emission sources, implications of urban sources, and the most studied countries, methodologies, limitations, and recommendations from different case studies. Our analysis reveals a significant research gap highlighting insufficient recent literature. Saudi Arabia was the most studied country with 20 papers, followed by the broader Arabian Peninsula (sixteen), Qatar (twelve), the United Arab Emirates and Iraq (seven each), Kuwait (four), Oman (three), Jordan, and Bahrain (one each). The primary methods employed included measurements and sampling (28%) and remote sensing (24%), with a focus on pollutants such as dust (23.1%), NO_x/NO₂/NO (17.2%), PM_2.5 (17.6%), and PM₁₀ (12%). Industrial emissions (27%) and natural dust (24%) were identified as significant emission sources. Monitoring methods included grab sampling (19%), integrated sampling (34%), and continuous monitoring (47%). Notably, 13.3% of AQ sensors were linked to a station, 27.6% were self-referenced, and 59.1% did not specify calibration methods. The findings highlight the need for further research, regular calibration of air quality monitors, and the integration of advanced modeling approaches. Moreover, we recommend exploring the links between air pollution and urban development to ensure cleaner air and contribute to the global dialogue on sustainable and cross-border AQ solutions. Full article

(This article belongs to the Section Air Quality)

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16 pages, 12472 KB

Open AccessEditor’s ChoiceArticle

Modeling and Accuracy Evaluation of Ionospheric VTEC Across China Utilizing CMONOC GPS/GLONASS Observations

by Fu-Ying Zhu and Chen Zhou

Atmosphere 2025, 16(8), 988; https://doi.org/10.3390/atmos16080988 - 20 Aug 2025

Viewed by 563

Abstract

Accurate estimation of the regional ionospheric model (RIM) is essential for Total electron content and high-precision applications of the Global Navigation Satellite System (GNSS). Utilizing dual-frequency observations from over 250 Crustal Movement Observation Network of China (CMONOC) monitoring stations, which are equipped with [...] Read more.

Accurate estimation of the regional ionospheric model (RIM) is essential for Total electron content and high-precision applications of the Global Navigation Satellite System (GNSS). Utilizing dual-frequency observations from over 250 Crustal Movement Observation Network of China (CMONOC) monitoring stations, which are equipped with both GPS and GLONASS receivers, this study investigates the Vertical Total Electron Content (VTEC) estimation models over the China region and evaluates the estimation accuracy under both GPS-only and GPS+GLONASS configurations. Results indicate that, over the Chinese region, the spherical harmonic reginal ionospheric model (G_SH RIM) and polynomial function reginal ionospheric model (G_Poly RIM) based on single GPS observations demonstrate comparable accuracy with highly consistent spatiotemporal distribution characteristics, showing grid mean deviations of 1.60 TECu and 1.62 TECu, respectively. The combined GPS+GLONASS observation-based RIMs (GR_SH RIM and GR_Poly RIM) significantly improve the TEC modeling accuracy in the Chinese peripheral regions, though the overall average accuracy decreases compared to single-GPS models. Specifically, GR_SH RIM and GR_Poly RIM exhibit mean deviations of 2.15 TECu and 2.32 TECu, respectively. A preliminary analysis reveals that the reduced accuracy is primarily due to the systematic errors introduced by imprecise differential code biases (DCBs) of GLONASS satellites. These findings can provide valuable references for multi-GNSS regional ionospheric estimation. Full article

(This article belongs to the Special Issue Advanced GNSS for Ionospheric Sounding and Disturbances Monitoring)

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23 pages, 3742 KB

Open AccessEditor’s ChoiceArticle

Emergency Medical Interventions in Areas with High Air Pollution: A Case Study from Małopolska Voivodeship, Poland

by Ewa Szewczyk, Michał Lupa, Mateusz Zaręba, Elżbieta Węglińska, Tomasz Danek and Amit Kumar Mishra

Atmosphere 2025, 16(8), 983; https://doi.org/10.3390/atmos16080983 - 18 Aug 2025

Viewed by 1464

Abstract

Air pollution poses a significant threat to public health, particularly in urban and industrialized regions. This study investigates the relationship between air quality and the frequency of Emergency Medical Service (EMS) calls in the Małopolska Voivodeship of Poland between 2020 and 2023. Data [...] Read more.

Air pollution poses a significant threat to public health, particularly in urban and industrialized regions. This study investigates the relationship between air quality and the frequency of Emergency Medical Service (EMS) calls in the Małopolska Voivodeship of Poland between 2020 and 2023. Data from over 190 air quality sensors (PM₁₀) were spatially aggregated using both hexagonal grids and administrative boundaries, while EMS call records were filtered to focus on cardiovascular and respiratory incidents. During 2020–2023, a total of 305,142 EMS calls were analyzed, and months with PM₁₀ exceedances showed an average of 1.50 respiratory calls per 1000 residents compared to 1.19 in months without exceedances. Statistical analyses, including Kolmogorov-Smirnov tests and Pearson correlation, were applied to explore temporal and spatial associations. Results indicate a statistically significant increase in EMS calls during periods of elevated air pollution, with the strongest correlation observed for respiratory-related incidents. Comparative analyses between high- and low-pollution municipalities supported the observed relationships. Further analysis indicated that the COVID-19 pandemic may have partially confounded these associations, particularly for respiratory cases, though significant patterns remained even after accounting for pandemic peaks. While limitations related to data gaps and seasonal biases exist, the findings suggest that real-time air pollution data could inform better EMS resource allocation. This research highlights the potential of integrating environmental data into public health strategies to improve emergency response and reduce health risks in polluted regions. Full article

(This article belongs to the Special Issue Advances in Air Pollution Data Analysis: From Classical Geostatistics to Big Data and Artificial Intelligence)

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19 pages, 3981 KB

Open AccessEditor’s ChoiceArticle

Dataset Construction for Radiative Transfer Modeling: Accounting for Spherical Curvature Effect on the Simulation of Radiative Transfer Under Diverse Atmospheric Scenarios

by Qingyang Gu, Kun Wu, Xinyi Wang, Qijia Xin and Luyao Chen

Atmosphere 2025, 16(8), 977; https://doi.org/10.3390/atmos16080977 - 17 Aug 2025

Viewed by 670

Abstract

Conventional radiative transfer (RT) models often adopt the plane-parallel (PP) approximation, which neglects Earth’s curvature and leads to significant optical path errors under large solar or sensor zenith angles, particularly for high-latitude regions and twilight conditions. The spherical Monte Carlo method offers high [...] Read more.

Conventional radiative transfer (RT) models often adopt the plane-parallel (PP) approximation, which neglects Earth’s curvature and leads to significant optical path errors under large solar or sensor zenith angles, particularly for high-latitude regions and twilight conditions. The spherical Monte Carlo method offers high accuracy but is computationally expensive, and the commonly used pseudo-spherical (PSS) approximation fails when the viewing zenith angle exceeds 80°. With the increasing application of machine learning in atmospheric science, the efficiency and angular limitations of spherical RT simulations may be overcome. This study provides a physical and quantitative foundation for developing a hybrid RT framework that integrates physical modeling with machine learning. By systematically quantifying the discrepancies between PP and spherical RT models under diverse atmospheric scenarios, key influencing factors—including wavelength, solar and viewing zenith angles, aerosol properties (e.g., single scattering albedo and asymmetry factor), and PP-derived radiance—were identified. These variables significantly affect spherical radiative transfer and serve as effective input features for data-driven models. Using the corresponding spherical radiance as the target variable, the proposed framework enables rapid and accurate inference of spherical radiative outputs based on computationally efficient PP simulations. Full article

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

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24 pages, 3586 KB

Open AccessEditor’s ChoiceArticle

Energy Sustainability of Urban Areas by Green Systems: Applied Thermodynamic Entropy and Strategic Modeling Means

by Carla Balocco, Giacomo Pierucci, Michele Baia, Costanza Borghi, Saverio Francini, Gherardo Chirici and Stefano Mancuso

Atmosphere 2025, 16(8), 975; https://doi.org/10.3390/atmos16080975 - 17 Aug 2025

Viewed by 852

Abstract

Global warming, anthropogenic pressure, and urban expansion at the expense of green spaces are leading to an increase in the incidence of urban heat islands, creating discomfort and health issue for citizens. This present research aimed at quantifying the impact of nature-based solutions [...] Read more.

Global warming, anthropogenic pressure, and urban expansion at the expense of green spaces are leading to an increase in the incidence of urban heat islands, creating discomfort and health issue for citizens. This present research aimed at quantifying the impact of nature-based solutions to support decision-making processes in sustainable energy action plans. A simple method is provided, linking applied thermodynamics to physics-informed modeling of urban built-up and green areas, high-resolution climate models at urban scale, greenery modeling, spatial georeferencing techniques for energy, and entropy exchanges evaluation in urban built-up areas, with and without vegetation. This allows the outdoor climate conditions and thermo-hygrometric well-being to improve, reducing the workload of cooling plant-systems in buildings and entropy flux to the environment. The finalization and post-processing of obtained results allows the definition of entropy footprints. The main findings show a decrease in greenery’s contribution for different scenarios, referring to a different climatological dataset, but an increase in entropy that becomes higher for the scenario with higher emissions. The comparison between the entropy footprint values for different urban zones can be a useful support to public administrations, stakeholders, and local governments for planning proactive resilient cities and anthropogenic impact reduction and climate change mitigation. Full article

(This article belongs to the Special Issue Advanced Studies on Climate Change in Urban Areas: Emerging Technologies and Strategies to Address Heat Waves and Improve Thermo-Hygrometric Comfort)

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24 pages, 8188 KB

Open AccessEditor’s ChoiceArticle

Top of the Atmosphere Reflected Shortwave Radiative Fluxes from ABI on GOES-18

by Yingtao Ma, Rachel T. Pinker, Wen Chen, Istvan Laszlo, Hye-Yun Kim, Hongqing Liu and Jaime Daniels

Atmosphere 2025, 16(8), 979; https://doi.org/10.3390/atmos16080979 - 17 Aug 2025

Viewed by 649

Abstract

In this study, we describe the derivation and evaluation of Top of the Atmosphere (TOA) Shortwave Radiative (SWR) Fluxes from the Advanced Baseline Imager (ABI) sensor on the GOES-18 satellite. The TOA estimates use narrowband observations from ABI that are transformed to broadband [...] Read more.

In this study, we describe the derivation and evaluation of Top of the Atmosphere (TOA) Shortwave Radiative (SWR) Fluxes from the Advanced Baseline Imager (ABI) sensor on the GOES-18 satellite. The TOA estimates use narrowband observations from ABI that are transformed to broadband (NTB), based on simulations and adjusted to total fluxes using Angular Distribution Models (ADMs). Subsequently, the GOES-18 estimates are evaluated against the Clouds and the Earth’s Radiant Energy System (CERES) data, the only observed SWR broadband flux dataset. The importance of agreement at the TOA is that most methodologies to derive surface SWR start with the satellite observation at the TOA. Moreover, information needed to compute radiative fluxes at both boundaries (TOA and surface) is needed for estimating the energy absorbed by the atmosphere. The methodology described was comprehensively evaluated, and possible sources of errors were identified. The results of the evaluation for the four seasonal months indicate that by using the best available auxiliary data, the accuracy achieved in estimating TOA SWR at the instantaneous scale ranges between 0.55 and 17.14 W m⁻² for the bias and 22.21 to 30.64 W m⁻² for the standard deviation of biases (differences are ABI minus CERES). It is believed that the high bias of 17.14 for July is related to the predominantly cloudless sky conditions, when the used ADMs do not perform as well as for cloudy conditions. Full article

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

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14 pages, 2723 KB

Open AccessEditor’s ChoiceArticle

Real-Time Insights into Indoor Air Quality in University Environments: PM and CO₂ Monitoring

by Dan-Marius Mustață, Daniel Bisorca, Ioana Ionel, Ahmed Adjal and Ramon-Mihai Balogh

Atmosphere 2025, 16(8), 972; https://doi.org/10.3390/atmos16080972 - 16 Aug 2025

Viewed by 1074

Abstract

This study presents real-time measurements of particulate matter (PM₁, PM_2.5, PM₁₀) and carbon dioxide (CO₂) concentrations across five university indoor environments with varying occupancy levels and natural ventilation conditions. CO₂ concentrations frequently exceeded the [...] Read more.

This study presents real-time measurements of particulate matter (PM₁, PM_2.5, PM₁₀) and carbon dioxide (CO₂) concentrations across five university indoor environments with varying occupancy levels and natural ventilation conditions. CO₂ concentrations frequently exceeded the 1000 ppm guideline, with peak values reaching 3018 ppm and 2715 ppm in lecture spaces, whereas one workshop environment maintained levels well below limits (mean = 668 ppm). PM concentrations varied widely: PM₁₀ reached 541.5 µg/m³ in a carpeted amphitheater, significantly surpassing the 50 µg/m³ legal daily limit, while a well-ventilated classroom exhibited lower levels despite moderate occupancy (PM₁₀ max = 116.9 µg/m³). Elevated PM values were strongly associated with flooring type and occupant movement, not just activity type. Notably, window ventilation during breaks reduced CO₂ concentrations by up to 305 ppm (p < 1 × 10⁻⁴⁷) and PM₁₀ by over 20% in rooms with favorable layouts. These findings highlight the importance of ventilation strategy, spatial orientation, and surface materials in shaping indoor air quality. The study emphasizes the need for targeted, non-invasive interventions to reduce pollutant exposure in historic university buildings where mechanical ventilation upgrades are often restricted. Full article

(This article belongs to the Special Issue Physical and Chemical Characterization of Particulate Matter: Ambient, Personal, and Indoor Perspectives)

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17 pages, 2613 KB

Open AccessEditor’s ChoiceArticle

Synergistic Effects of Ambient PM_2.5 and O₃ with Natural Temperature Variability on Non-Accidental and Cardiovascular Mortality: A Historical Time Series Analysis in Urban Taiyuan, China

by Huan Zhou, Hong Geng, Jingjing Tian, Li Wu, Zhihong Zhang and Daizhou Zhang

Atmosphere 2025, 16(8), 971; https://doi.org/10.3390/atmos16080971 - 15 Aug 2025

Viewed by 635

Abstract

Climate change and air pollution are associated with a range of health outcomes, including cardiovascular and respiratory disease. Evaluation of the synergic effects of air pollution and increasing natural temperature on mortality is important for understanding their potential joint health effects. In this [...] Read more.

Climate change and air pollution are associated with a range of health outcomes, including cardiovascular and respiratory disease. Evaluation of the synergic effects of air pollution and increasing natural temperature on mortality is important for understanding their potential joint health effects. In this study, the modification effects of air temperature on the short-term association of ambient fine particulate matter (PM_2.5) and ozone (O₃) with non-accidental death (NAD) and cardiovascular disease (CVD) mortality were evaluated by using the generalized additive model (GAM) combined with the distributed lag nonlinear model (DLNM) in urban areas of Taiyuan, a representative of energy and heavy industrial cities in Northern China. The data on the daily cause-specific death numbers, air pollutants concentrations, and meteorological factors were collected from January 2013 to December 2019, and the temperature was divided into low (<25th percentile), medium (25–75th percentile), and high (>75th percentile) categories. Significant associations of PM_2.5 and O₃ with NAD and CVD mortality were observed in single-effect analysis. A statistically significant increase in the effect estimates of PM_2.5 and O₃ on NAD and CVD mortality was also observed on high-temperature days. But the associations of those were not statistically significant on medium- and low-temperature days. At the same temperature level, the effects of PM_2.5 and O₃ on the CVD mortality were larger than those on NAD (1.74% vs. 1.21%; 1.67% vs. 0.57%), and the elderly and males appeared to be more vulnerable to both higher temperatures and air pollution. The results suggest that the acute effect of PM_2.5 and O₃ on NAD and CVD mortality in urban Taiyuan was enhanced by increasing temperatures, particularly for the elderly and males. It highlights the importance of reducing PM_2.5 and O₃ exposure in urban areas to reduce the public health burden under the situation of global warming. Full article

(This article belongs to the Special Issue Composition Analysis and Health Effects of Atmospheric Particulate Matter (2nd Edition))

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19 pages, 7660 KB

Open AccessEditor’s ChoiceArticle

The Impact of Photochemical Loss on the Source Apportionment of Ambient Volatile Organic Compounds (VOCs) and Their Ozone Formation Potential in the Fenwei Plain, Northern China

by Yanan Tao, Qi Xiong, Yawei Dong, Jiayin Zhang, Lei Cao, Min Zhu, Qiaoqiao Wang and Jianwei Gu

Atmosphere 2025, 16(8), 970; https://doi.org/10.3390/atmos16080970 - 15 Aug 2025

Viewed by 892

Abstract

The Fenwei Plain (FWP), one of China’s most polluted regions, has experienced severe ozone (O₃) pollution in recent years. Volatile organic compounds (VOCs), key O₃ precursors, undergo significant photochemical degradation, yet their loss and the implications for source apportionment and [...] Read more.

The Fenwei Plain (FWP), one of China’s most polluted regions, has experienced severe ozone (O₃) pollution in recent years. Volatile organic compounds (VOCs), key O₃ precursors, undergo significant photochemical degradation, yet their loss and the implications for source apportionment and ozone formation potential (OFP) in this region remain unclear. This study conducted summertime VOC measurements in two industrial cities in the FWP, Hancheng (HC) and Xingping (XP), to quantify photochemical losses of VOCs and assessed their impact on source attribution and OFP with photochemical age-based parameterization methods. Significant VOC photochemical losses were observed, averaging 3.6 ppbv (7.1% of initial concentrations) in HC and 1.9 ppbv (5.6%) in XP, with alkenes experiencing the highest depletion (22–30%). Source apportionment based on both initial (corrected) and observed concentrations revealed that industrial sources (e.g., coking, coal washing, and rubber manufacturing) dominated ambient VOCs. Ignoring photochemical losses underestimated contributions from natural gas combustion and biogenic sources, while it overestimated the secondary source. OFP calculated with lost VOCs (OFP_loss) reached 34 ppbv in HC and 15 ppbv in XP, representing 20% and 25% of OFP based on observed concentrations, respectively, with reactive alkenes accounting for over 90% of OFPloss. The results highlight the importance of accounting for VOC photochemical losses for accurate source identification and developing effective O₃ control strategies in the FWP. Full article

(This article belongs to the Section Air Quality)

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24 pages, 9802 KB

Open AccessEditor’s ChoiceArticle

Threshold Dynamics of Vegetation Carbon Sink Loss Under Multiscale Droughts in the Mongolian Plateau

by Hongguang Chen, Mulan Wang, Fanhao Meng, Chula Sa, Min Luo, Wenfeng Chi and Sonomdagva Chonokhuu

Atmosphere 2025, 16(8), 964; https://doi.org/10.3390/atmos16080964 - 14 Aug 2025

Viewed by 617

Abstract

Gross primary productivity (GPP) is a key carbon flux in the global carbon cycle, and understanding the inhibitory effects of drought on GPP and its underlying mechanisms is crucial for understanding carbon–climate feedback. However, current research has not sufficiently addressed the threshold dynamics [...] Read more.

Gross primary productivity (GPP) is a key carbon flux in the global carbon cycle, and understanding the inhibitory effects of drought on GPP and its underlying mechanisms is crucial for understanding carbon–climate feedback. However, current research has not sufficiently addressed the threshold dynamics and regional differentiation of GPP responses to the synergistic effects of meteorological drought (MD) and soil moisture drought (SD), particularly in the drought-sensitive Mongolian Plateau. This study focuses on the Mongolian Plateau from 1982 to 2021, using the standardized precipitation index (SPI) and standardized soil moisture index (SSI) to characterize MD and SD, respectively. The study combines the three-threshold run theory, cross-wavelet analysis, Spearman correlation analysis, and copula models to systematically investigate the variation characteristics, propagation patterns, and the probability and thresholds for triggering GPP loss under different time scales (monthly, seasonal, semi-annual, and annual). The results show that (1) both types of droughts exhibited significant intensification trends, with SD intensifying at a faster rate (annual scale SSI12 trend: −0.34/10a). The intensification trend strengthened with increasing time scales. MD exhibited high frequency, short duration, and low intensity, while SD showed the opposite characteristics. The most significant aridification occurred in the central region. (2) The average propagation time from MD to SD was 11.22 months. The average response time of GPP to MD was 10.46 months, while the response time to SD was significantly shorter (approximately 2 months on average); the correlation between SSI and GPP was significantly higher than that between SPI and GPP. (3) The conditional probability of triggering mild GPP loss (e.g., <40^th percentile) was relatively high for both drought types, and the probability of loss increased as the time scales extended. Compared to MD, SD was more likely to induce severe GPP loss. Additionally, the drought intensity threshold for triggering mild loss was lower (i.e., mild drought could trigger it), while higher drought intensity was required to trigger severe and extreme losses. Therefore, this study provides practical guidance for regional drought early-warning systems and ecosystem adaptive management, while laying an important theoretical foundation for a deeper understanding of drought response mechanisms. Full article

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

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13 pages, 2696 KB

Open AccessEditor’s ChoiceArticle

Chemistry of Precipitation Acidity at Irkutsk, Russia

by Hiroshi Hara and Izumi Noguchi

Atmosphere 2025, 16(8), 959; https://doi.org/10.3390/atmos16080959 - 12 Aug 2025

Viewed by 636

Abstract

Precipitation pH at a Russin EANET site, Irkutsk, was discussed and explained from the viewpoint of acid–base chemical equilibrium theory. The datasets employed were the wet-only daily basis observations at a subarctic climate urban site from 1999 to 2020. A distinct seasonal variation [...] Read more.

Precipitation pH at a Russin EANET site, Irkutsk, was discussed and explained from the viewpoint of acid–base chemical equilibrium theory. The datasets employed were the wet-only daily basis observations at a subarctic climate urban site from 1999 to 2020. A distinct seasonal variation in pH was discovered for the monthly means over the entire period, from pH5.24 in July to pH6.66 in February, bracketing pH5.6, a criterion for acid rain. Monthly concentration variations in major ions, nss-SO₄²⁻, NO₃⁻, NH₄⁺, and nss-Ca²⁺, divulged that nss-Ca²⁺ and nss-SO₄²⁻ were predominant species and that nss-Ca²⁺ dominated nss-SO₄²⁻ during winter months and vice versa in summer. Individual pHs were explored with the concentration difference between two ions, ([nss-SO₄²⁻] − [nss-Ca²⁺]), defined as D₂, as well as two other differences in selected ion groups, D₄ = ([nss-SO₄²⁻] + [NO₃⁻]) − ([NH₄⁺] + [nss-Ca²⁺]) and D₆ = ([nss-SO₄²⁻] + [NO₃⁻]) − ([NH₄⁺] + [nss-Ca²⁺] + [nss-Mg²⁺] + [nss-K⁺]), to show some clear relationships with pH. The observed results were compared with theoretical calculations, D_n = [H⁺] − HP_CO2K_a1/[H⁺], where n is 2, 4, or 6. The distribution of ΔpH (=pH_calc − pH_obs) for D₂ demonstrated the most reasonable pattern with a median of zero among the three D_ns. These quantitative results conclude that the Irkutsk pH was controlled dominantly by sulfuric acid and calcium carbonate. Full article

(This article belongs to the Section Air Quality)

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17 pages, 7328 KB

Open AccessEditor’s ChoiceArticle

Coastal Wind in East Iceland Using Sentinel-1 and Model Data Reanalysis

by Eduard Khachatrian, Yngve Birkelund and Andrea Marinoni

Atmosphere 2025, 16(8), 962; https://doi.org/10.3390/atmos16080962 - 12 Aug 2025

Cited by 1 | Viewed by 686

Abstract

This study evaluates three wind data sources in East Iceland’s coastal environment: the high-resolution Synthetic Aperture Radar (SAR)-based Sentinel-1, the regional reanalysis Copernicus Arctic Regional Reanalysis (CARRA), and the global reanalysis ECMWF Reanalysis v5 (ERA5). We focus on assessing the advantages and limitations [...] Read more.

This study evaluates three wind data sources in East Iceland’s coastal environment: the high-resolution Synthetic Aperture Radar (SAR)-based Sentinel-1, the regional reanalysis Copernicus Arctic Regional Reanalysis (CARRA), and the global reanalysis ECMWF Reanalysis v5 (ERA5). We focus on assessing the advantages and limitations of each dataset, especially considering their differences in spatial and temporal resolutions. While ERA5 aligns well with CARRA and Sentinel-1 offshore, it tends to underestimate wind speeds and misrepresent wind directions near complex coastlines and fjords, with Root Mean Squared Difference (RMSD) values reaching up to 3.98 m/s in these areas. CARRA’s higher resolution allows it to better capture coastal wind dynamics and shows strong agreement with Sentinel-1. Sentinel-1 excels in revealing detailed local wind features, such as katabatic winds in fjords, highlighting the value of satellite observations in complex terrain. By combining these complementary datasets, this study enhances understanding of coastal wind variability and supports improved hazard assessment in Iceland’s challenging coastal environments. Full article

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

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11 pages, 2212 KB

Open AccessEditor’s ChoiceArticle

Vertical Evolution of Volatile Organic Compounds from Unmanned Aerial Vehicle Measurements in the Pearl River Delta, China

by Meng-Xue Tang, Bi-Xuan Wang, Yong Cheng, Hui Zeng and Xiao-Feng Huang

Atmosphere 2025, 16(8), 955; https://doi.org/10.3390/atmos16080955 - 10 Aug 2025

Viewed by 629

Abstract

The vertical distribution of volatile organic compounds (VOCs) within the planetary boundary layer (PBL) is critical for understanding ozone (O₃) formation, yet knowledge remains limited in complex urban environments. In this study, vertical measurements of 117 VOC species were conducted using [...] Read more.

The vertical distribution of volatile organic compounds (VOCs) within the planetary boundary layer (PBL) is critical for understanding ozone (O₃) formation, yet knowledge remains limited in complex urban environments. In this study, vertical measurements of 117 VOC species were conducted using an unmanned aerial vehicle (UAV) equipped with a VOC multi-channel sampling system, up to a height of 500 m in Shenzhen, China. Results showed that total VOC (TVOC) concentrations decreased with altitude in the morning, reflecting the influence of surface-level local emissions, but increased with height at midday, likely driven by regional transport and potentially stronger photochemical processes. Source apportionment revealed substantial industrial emissions across all altitudes, vehicular emissions concentrated near the surface, and biomass burning primarily impacting higher layers. Clear evidence of enhanced secondary formation of oxygenated VOCs (OVOCs) was observed along the vertical gradient, particularly at midday, indicating intensified photochemical processes at higher altitudes. These findings underscore the importance of considering vertical heterogeneity in VOC distributions when modeling O₃ formation or developing measures to reduce emissions at different altitudes, and also demonstrate the potential of UAV platforms to provide high-resolution atmospheric chemical data in complex urban environments. Full article

(This article belongs to the Special Issue Biogenic Volatile Organic Compound: Measurement and Emissions)

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22 pages, 7438 KB

Open AccessEditor’s ChoiceArticle

Expanding Continuous Carbon Isotope Measurements of CO₂ and CH₄ in the Italian ICOS Atmospheric Consortium: First Results from the Continental POT Station in Potenza (Basilicata)

by Antonella Buono, Isabella Zaccardo, Francesco D’Amico, Emilio Lapenna, Francesco Cardellicchio, Teresa Laurita, Davide Amodio, Canio Colangelo, Gianluca Di Fiore, Aldo Giunta, Michele Volini, Claudia Roberta Calidonna, Alcide Giorgio di Sarra, Serena Trippetta and Lucia Mona

Atmosphere 2025, 16(8), 951; https://doi.org/10.3390/atmos16080951 - 8 Aug 2025

Cited by 2 | Viewed by 947

Abstract

Carbon isotope fractionation is an efficient tool used for the discrimination and differentiation of sinks and emission sources. Carbon dioxide (CO₂) and methane (CH₄) are among the key drivers of climate change, and a detailed evaluation of variations in [...] Read more.

Carbon isotope fractionation is an efficient tool used for the discrimination and differentiation of sinks and emission sources. Carbon dioxide (CO₂) and methane (CH₄) are among the key drivers of climate change, and a detailed evaluation of variations in the ¹³C/¹²C ratio in either compound provides vital information for the field of atmospheric sciences. The Italian atmospheric ICOS (Integrated Carbon Observation System) consortium is currently implementing δ¹³C-CO₂ and δ¹³C-CH₄ measurements, with four observation sites now equipped with Picarro G2201-i CRDS (Cavity Ring-Down Spectrometry) analyzers. In this work, results from the first two months of measurements performed at the Potenza station in southern Italy between 20 February and 20 April 2025 are presented and constitute the first evaluation of continuous atmospheric δ¹³C-CO₂ and δ¹³C-CH₄ measurements from an Italian station. These results provide a first insight on how these measurements can improve the current understanding of CO₂ and CH₄ variability in the Italian peninsula and the central Mediterranean sector. Although preliminary in nature, the findings of these measurements indicate that fossil fuel burning is responsible for the observed peaks in CO₂ concentrations. CH₄ has a generally stable pattern; however, abrupt peaks in its isotopic delta, observed during March, may constitute the first direct evidence in Italy of Saharan dust intrusion affecting carbon isotope fractionation in the atmosphere. This study also introduces an analysis of the weekly behavior in isotopic deltas. Full article

(This article belongs to the Section Air Pollution Control)

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16 pages, 18507 KB

Open AccessEditor’s ChoiceArticle

Spatiotemporal Ionospheric TEC Prediction with Deformable Convolution for Long-Term Spatial Dependencies

by Jie Li, Jian Xiao, Haijun Liu, Xiaofeng Du and Shixiang Liu

Atmosphere 2025, 16(8), 950; https://doi.org/10.3390/atmos16080950 - 7 Aug 2025

Viewed by 453

Abstract

SA-ConvLSTM is a recently proposed spatiotemporal model for total electron content (TEC) prediction, which effectively catches long-term temporal evolution and global-scale spatial correlations in TEC. However, its reliance on standard convolution limits spatial feature extraction to fixed regular regions, reducing the flexibility for [...] Read more.

SA-ConvLSTM is a recently proposed spatiotemporal model for total electron content (TEC) prediction, which effectively catches long-term temporal evolution and global-scale spatial correlations in TEC. However, its reliance on standard convolution limits spatial feature extraction to fixed regular regions, reducing the flexibility for irregular TEC variations. To address this limitation, we enhance SA-ConvLSTM by incorporating deformable convolution, proposing SA-DConvLSTM. This achieves adaptive spatial feature extraction through learnable offsets in convolutional kernels. Building on this improvement, we design ED-SA-DConvLSTM, a TEC spatiotemporal prediction model based on an encoder–decoder architecture with SA-DConvLSTM as its fundamental block. Firstly, the effectiveness of the model improvement was verified through an ablation experiment. Subsequently, a comprehensive quantitative comparison was conducted between ED-SA-DConvLSTM and baseline models (C1PG, ConvLSTM, and ConvGRU) in the region of 12.5° S–87.5° N and 25° E–180° E. The experimental results showed that the ED-SA-DConvLSTM exhibited superior performance compared to C1PG, ConvGRU, and ConvLSTM, with prediction accuracy improvements of 10.27%, 7.65%, and 7.16% during high solar activity and 11.46%, 4.75%, and 4.06% during low solar activity, respectively. To further evaluate model performance under extreme conditions, we tested the ED-SA-DConvLSTM during four geomagnetic storms. The results showed that the proportion of its superiority over the baseline models exceeded 58%. Full article

(This article belongs to the Section Upper Atmosphere)

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23 pages, 11564 KB

Open AccessEditor’s ChoiceArticle

Cloud-Based Assessment of Flash Flood Susceptibility, Peak Runoff, and Peak Discharge on a National Scale with Google Earth Engine (GEE)

by Ivica Milevski, Bojana Aleksova, Aleksandar Valjarević and Pece Gorsevski

Atmosphere 2025, 16(8), 945; https://doi.org/10.3390/atmos16080945 - 7 Aug 2025

Cited by 2 | Viewed by 1547

Abstract

Flash floods, exacerbated by climate change and land use alterations, are among the most destructive natural hazards globally, leading to significant damage and loss of life. In this context, the Flash Flood Potential Index (FFPI), which is a terrain and land surface-based model, [...] Read more.

Flash floods, exacerbated by climate change and land use alterations, are among the most destructive natural hazards globally, leading to significant damage and loss of life. In this context, the Flash Flood Potential Index (FFPI), which is a terrain and land surface-based model, and Google Earth Engine (GEE) were used to assess flood-prone zones across North Macedonia’s watersheds. The presented GEE-based assessment was accomplished by a custom script that automates the FFPI calculation process by integrating key factors derived from publicly available sources. These factors, which define susceptibility to torrential floods, include slope (Copernicus GLO-30 DEM), land cover (Copernicus GLO-30 DEM), soil type (SoilGrids), vegetation (ESA World Cover), and erodibility (CHIRPS). The spatial distribution of average FFPI values across 1396 small catchments (10–100 km²) revealed that a total of 45.4% of the area exhibited high to very high susceptibility, with notable spatial variability. The CHIRPS rainfall data (2000–2024) that combines satellite imagery and in situ measurements was used to estimate peak 24 h runoff and discharge. To improve the accuracy of CHIRPS, the data were adjusted by 30–50% to align with meteorological station records, along with normalized FFPI values as runoff coefficients. Validation against 328 historical river flood and flash flood records confirmed that 73.2% of events aligned with moderate to very high flash flood susceptibility catchments, underscoring the model’s reliability. Thus, the presented cloud-based scenario highlights the potential of the GEE’s efficacy in scalability and robustness for flash flood modeling and regional risk management at national scale. Full article

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

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12 pages, 1678 KB

Open AccessEditor’s ChoiceArticle

Fine-Scale Spatial Distribution of Indoor Radon and Identification of Potential Ingress Pathways

by Dobromir Pressyanov and Dimitar Dimitrov

Atmosphere 2025, 16(8), 943; https://doi.org/10.3390/atmos16080943 - 6 Aug 2025

Viewed by 486

Abstract

A new generation of compact radon detectors with high sensitivity and fine spatial resolution (1–2 cm scale) was used to investigate indoor radon distribution and identify potential entry pathways. Solid-state nuclear track detectors (Kodak-Pathe LR-115 type II, Dosirad, France), combined with activated carbon [...] Read more.

A new generation of compact radon detectors with high sensitivity and fine spatial resolution (1–2 cm scale) was used to investigate indoor radon distribution and identify potential entry pathways. Solid-state nuclear track detectors (Kodak-Pathe LR-115 type II, Dosirad, France), combined with activated carbon fabric (ACC-5092-10), enabled sensitive, spatially resolved radon measurements. Two case studies were conducted: Case 1 involves a room with elevated radon levels suspected to originate from the floor. Case 2 involves a house with persistently high indoor radon concentrations despite active basement ventilation. In the first case, radon emission from the floor was found to be highly inhomogeneous, with concentrations varying by more than a factor of four. In the second, unexpectedly high radon levels were detected at electrical switches and outlets on walls in the living space, suggesting radon transport through wall voids and entry via non-hermetic electrical fittings. These novel detectors facilitate fine-scale mapping of indoor radon concentrations, revealing ingress routes that were previously undetectable. Their use can significantly enhance radon diagnostics and support the development of more effective mitigation strategies. Full article

(This article belongs to the Special Issue Atmospheric Radon Concentration Monitoring and Measurements (2nd Edition))

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30 pages, 9610 KB

Open AccessEditor’s ChoiceArticle

Can the Building Make a Difference to User’s Health in Indoor Environments? The Influence of PM_2.5 Vertical Distribution on the IAQ of a Student House over Two Periods in Milan in 2024

by Yong Yu, Marco Gola, Gaetano Settimo and Stefano Capolongo

Atmosphere 2025, 16(8), 936; https://doi.org/10.3390/atmos16080936 - 4 Aug 2025

Viewed by 702

Abstract

This study investigates indoor and outdoor air quality monitoring in a student dormitory located in northern Milan (Italy) using low-cost sensors. This research compares two monitoring periods in June and October 2024 to examine common PM_2.5 vertical patterns and differences at the [...] Read more.

This study investigates indoor and outdoor air quality monitoring in a student dormitory located in northern Milan (Italy) using low-cost sensors. This research compares two monitoring periods in June and October 2024 to examine common PM_2.5 vertical patterns and differences at the building level, as well as their influence on the indoor spaces at the corresponding positions. In each period, around 30 sensors were installed at various heights and orientations across indoor and outdoor spots for 2 weeks to capture spatial variations around the building. Meanwhile, qualitative surveys on occupation presence, satisfaction, and well-being were distributed in selected rooms. The analysis of PM_2.5 data reveals that the building’s lower floors tended to have slightly higher outdoor PM_2.5 concentrations, while the upper floors generally had lower PM_2.5 indoor/outdoor (I/O) ratios, with the top-floor rooms often below 1. High outdoor humidity reduced PM infiltration, but when outdoor PM fell below 20 µg/m³ in these two periods, indoor sources became dominant, especially on the lower floors. Air pressure I/O differences had minimal impact on PM_2.5 I/O ratios, though slightly positive indoor pressure might help prevent indoor PM infiltration. Lower ventilation in Period-2 possibly contributed to more reported symptoms, especially in rooms with higher PM from shared kitchens. While outdoor air quality affects IAQ, occupant behavior—especially window opening and ventilation management—remains crucial in minimizing indoor pollutants. Users can also manage exposure by ventilating at night based on comfort and avoiding periods of high outdoor PM. Full article

(This article belongs to the Special Issue Air Quality in Metropolitan Areas and Megacities (Second Edition))

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23 pages, 5566 KB

Open AccessEditor’s ChoiceArticle

Response Mechanisms of Vegetation Productivity to Water Variability in Arid and Semi-Arid Areas of China: A Decoupling Analysis of Soil Moisture and Precipitation

by Zijian Liu, Hao Lin, Hongrui Li, Mengyang Li, Peng Zhou, Ziyu Wang and Jiqiang Niu

Atmosphere 2025, 16(8), 933; https://doi.org/10.3390/atmos16080933 - 3 Aug 2025

Cited by 1 | Viewed by 592

Abstract

Arid and semi-arid areas serve a critical regulatory function within the global carbon cycle. Understanding the response mechanisms of vegetation productivity to variations in moisture availability represents a fundamental scientific challenge in elucidating terrestrial carbon dynamics. This study systematically disentangled the respective influences [...] Read more.

Arid and semi-arid areas serve a critical regulatory function within the global carbon cycle. Understanding the response mechanisms of vegetation productivity to variations in moisture availability represents a fundamental scientific challenge in elucidating terrestrial carbon dynamics. This study systematically disentangled the respective influences of summer surface soil moisture (RSM) and precipitation (PRE) on gross primary productivity (GPP) across arid and semi-arid regions of China from 2000 to 2022. Utilizing GPP datasets alongside correlation analysis, ridge regression, and data binning techniques, the investigation yielded several key findings: (1) Both GPP and RSM exhibited significant upward trends within the study area, whereas precipitation showed no statistically significant trend; notably, GPP demonstrated the highest rate of increase at 0.455 Cg m⁻² a⁻¹. (2) Decoupling analysis indicated a coupled relationship between RSM and PRE; however, their individual effects on GPP were not merely a consequence of this coupling. Controlling for evapotranspiration and root-zone soil moisture interference, the analysis revealed that under conditions of elevated RSM, the average increase in summer–autumn GPP (SA_GPP) was 0.249, significantly surpassing the increase observed under high-PRE conditions (−0.088). Areas dominated by RSM accounted for 62.13% of the total study region. Furthermore, examination of the aridity gradient demonstrated that the predominance of RSM intensified with increasing aridity, reaching its peak influence in extremely arid zones. This research provides a quantitative assessment of the differential impacts of RSM and PRE on vegetation productivity in China’s arid and semi-arid areas, thereby offering a vital theoretical foundation for improving predictions of terrestrial carbon sink dynamics under future climate change scenarios. Full article

(This article belongs to the Special Issue Climate Change and Regional Sustainability in Arid Lands (2nd Edition))

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27 pages, 15404 KB

Open AccessEditor’s ChoiceArticle

Machine-Learning Models for Surface Ozone Forecast in Mexico City

by Mateen Ahmad, Bernhard Rappenglück, Olabosipo O. Osibanjo and Armando Retama

Atmosphere 2025, 16(8), 931; https://doi.org/10.3390/atmos16080931 - 1 Aug 2025

Viewed by 967

Abstract

Mexico City frequently experiences high near-surface ozone concentrations, and exposure to elevated near-surface ozone causes harmful effects to the inhabitants and the environment of Mexico City. This necessitates developing models for Mexico City that predict near-surface ozone levels in advance. Such models are [...] Read more.

Mexico City frequently experiences high near-surface ozone concentrations, and exposure to elevated near-surface ozone causes harmful effects to the inhabitants and the environment of Mexico City. This necessitates developing models for Mexico City that predict near-surface ozone levels in advance. Such models are crucial for regulatory procedures and can save a great deal of near-surface ozone detrimental effects by serving as early warning systems. We utilize three machine-learning models, trained on seven-year data (2015–2021) and tested on one-year data (2022), to forecast the near-surface ozone concentrations. The trained models predict the next day’s 24-h near-surface ozone concentrations for up to one month; before forecasting the following months, the models are trained again and updated. Based on prediction results, the convolutional neural network outperforms the rest of the models on a yearly scale with an index of agreement of 0.93 for three stations, 0.92 for nine stations, and 0.91 for one station. Full article

(This article belongs to the Special Issue Advances in Air Pollution Data Analysis: From Classical Geostatistics to Big Data and Artificial Intelligence)

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18 pages, 3114 KB

Open AccessEditor’s ChoiceArticle

Heavy Rainfall Induced by Typhoon Yagi-2024 at Hainan and Vietnam, and Dynamical Process

by Venkata Subrahmanyam Mantravadi, Chen Wang, Bryce Chen and Guiting Song

Atmosphere 2025, 16(8), 930; https://doi.org/10.3390/atmos16080930 - 1 Aug 2025

Viewed by 2034

Abstract

Typhoon Yagi (2024) was a rapidly moving storm that lasted for eight days and made landfall in three locations, producing heavy rainfall over Hainan and Vietnam. This study aims to investigate the dynamical processes contributing to the heavy rainfall, concentrating on enthalpy flux [...] Read more.

Typhoon Yagi (2024) was a rapidly moving storm that lasted for eight days and made landfall in three locations, producing heavy rainfall over Hainan and Vietnam. This study aims to investigate the dynamical processes contributing to the heavy rainfall, concentrating on enthalpy flux (EF) and moisture flux (MF). The results indicate that both EF and MF increased significantly during the typhoon’s intensification stage and were high at the time of landfall. Before landfalling at Hainan, latent heat flux (LHF) reached 600 W/m², while sensible heat flux (SHF) was recorded as 80 W/m². Landfall at Hainan resulted in a decrease in LHF and SHF. LHF and SHF subsequently increased to 700 W/m² and 100 W/m², respectively, as noted prior to the landfall in Vietnam. The increased LHF led to higher evaporation, which subsequently elevated moisture flux (MF) following the landfall in Vietnam, while the region’s topography further intensified the rainfall. The mean daily rainfall observed over Philippines is 75 mm on 2 September (landfall and passing through), 100 mm over Hainan (landfall and passing through) on 6 September, and 95 mm at over Vietnam on 7 September (landfall and after), respectively. Heavy rainfall was observed over the land while the typhoon was passing and during the landfall. This research reveals that Typhoon Yagi’s intensity was maintained by a well-organized and extensive circulation system, supported by favorable weather conditions, including high sea surface temperatures (SST) exceeding 30.5 °C, substantial low-level moisture convergence, and elevated EF during the landfall in Vietnam. Full article

(This article belongs to the Section Meteorology)

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21 pages, 3828 KB

Open AccessEditor’s ChoiceArticle

Can a Global Climate Model Reproduce a Tornado Outbreak Atmospheric Pattern? Methodology and a Case Study

by Paulina Ćwik, Renee A. McPherson, Funing Li and Jason C. Furtado

Atmosphere 2025, 16(8), 923; https://doi.org/10.3390/atmos16080923 - 30 Jul 2025

Viewed by 501

Abstract

Tornado outbreaks can cause substantial damage, injuries, and fatalities, highlighting the need to understand their characteristics for assessing present and future risks. However, global climate models (GCMs) lack the resolution to explicitly simulate tornado outbreaks. As an alternative, researchers examine large-scale atmospheric ingredients [...] Read more.

Tornado outbreaks can cause substantial damage, injuries, and fatalities, highlighting the need to understand their characteristics for assessing present and future risks. However, global climate models (GCMs) lack the resolution to explicitly simulate tornado outbreaks. As an alternative, researchers examine large-scale atmospheric ingredients that approximate tornado-conducive environments. Building on this approach, we tested whether patterns of covariability between WMAXSHEAR and 500-hPa geopotential height anomalies, previously identified in ERA5 reanalysis, could approximate major U.S. May tornado outbreaks in a GCM. We developed a proxy-based methodology by systematically testing pairs of thresholds for both variables to identify the combination that best reproduced the leading pattern selected for analysis. These thresholds were then applied to simulations from the high-resolution MPI-ESM1.2-HR model to assess its ability to reproduce the original pattern. Results show that the model closely mirrored the observed tornado outbreak pattern, as indicated by a low normalized root mean square error, high spatial correlation, and similar distributions. This study demonstrates a replicable approach for approximating tornado outbreak patterns, applied here to the leading pattern, within a GCM, providing a foundation for future research on how such environments might evolve in a warming climate. Full article

(This article belongs to the Section Meteorology)

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14 pages, 2075 KB

Open AccessEditor’s ChoiceArticle

Quantifying Polar Mesospheric Clouds Thermal Impact on Mesopause

by Arseniy Sokolov, Elena Savenkova, Andrey Koval, Nikolai Gavrilov, Karina Kravtsova, Kseniia Didenko and Tatiana Ermakova

Atmosphere 2025, 16(8), 922; https://doi.org/10.3390/atmos16080922 - 30 Jul 2025

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Abstract

The article is focused on the quantitative assessment of the thermal impact of polar mesospheric clouds (PMCs) on the mesopause caused by the emission of absorbed solar and terrestrial infrared (IR) radiation by cloud particles. For this purpose, a parameterization of mesopause heating [...] Read more.

The article is focused on the quantitative assessment of the thermal impact of polar mesospheric clouds (PMCs) on the mesopause caused by the emission of absorbed solar and terrestrial infrared (IR) radiation by cloud particles. For this purpose, a parameterization of mesopause heating by PMC crystals has been developed, the main feature of which is to incorporate the thermal properties of ice and the interaction of cloud particles with the environment. Parametrization is based on PMCs zero-dimensional (0-D) model and uses temperature, pressure, and water vapor data in the 80–90 km altitude range retrieved from Solar Occultation for Ice Experiment (SOFIE) measurements. The calculations are made for 14 PMC seasons in both hemispheres with the summer solstice as the central date. The obtained results show that PMCs can make a significant contribution to the heat balance of the upper atmosphere, comparable to the heating caused, for example, by the dissipation of atmospheric gravity waves (GWs). The interhemispheric differences in heating are manifested mainly in the altitude structure: in the Southern Hemisphere (SH), the area of maximum heating values is 1–2 km higher than in the Northern Hemisphere (NH), while quantitatively they are of the same order. The most intensive heating is observed at the lower boundary of the minimum temperature layer (below 150 K) and gradually weakens with altitude. The NH heating median value is 5.86 K/day, while in the SH it is 5.24 K/day. The lowest values of heating are located above the maximum of cloud ice concentration in both hemispheres. The calculated heating rates are also examined in the context of the various factors of temperature variation in the observed atmospheric layers. It is shown in particular that the thermal impact of PMC is commensurate with the influence of dissipating gravity waves at heights of the mesosphere and lower thermosphere (MLT), which parameterizations are included in all modern numerical models of atmospheric circulation. Hence, the developed parameterization can be used in global atmospheric circulation models for further study of the peculiarities of the thermodynamic regime of the MLT. Full article

(This article belongs to the Special Issue Observations and Analysis of Upper Atmosphere (2nd Edition))

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29 pages, 16630 KB

Open AccessEditor’s ChoiceArticle

Impact of Radar Data Assimilation on the Simulation of Typhoon Morakot

by Lingkun Ran and Cangrui Wu

Atmosphere 2025, 16(8), 910; https://doi.org/10.3390/atmos16080910 - 28 Jul 2025

Viewed by 472

Abstract

The high spatial resolution of radar data enables the detailed resolution of typhoon vortices and their embedded structures; the assimilation of radar data in the initialization of numerical weather prediction exerts an important influence on the forecasting of typhoon track, intensity, and structures [...] Read more.

The high spatial resolution of radar data enables the detailed resolution of typhoon vortices and their embedded structures; the assimilation of radar data in the initialization of numerical weather prediction exerts an important influence on the forecasting of typhoon track, intensity, and structures up to at least 12 h. For the case of typhoon Morakot (2009), Taiwan radar data was assimilated to adjust the dynamic and thermodynamic structures of the vortex in the model initialization by the three-dimensional variation data assimilation system in the Advanced Region Prediction System (ARPS). The radial wind was directly assimilated to tune the original unbalanced velocity fields through a 3-dimensional variation method, and complex cloud analysis was conducted by using the reflectivity data. The influence of radar data assimilation on typhoon prediction was examined at the stages of Morakot landing on Taiwan Island and subsequently going inland. The results showed that the assimilation made some improvement in the prediction of vortex intensity, track, and structures in the initialization and subsequent forecast. For example, besides deepening the central sea level pressure and enhancing the maximum surface wind speed, the radar data assimilation corrected the typhoon center movement to the best track and adjusted the size and inner-core structure of the vortex to be close to the observations. It was also shown that the specific humidity adjustment in the cloud analysis procedure during the assimilation time window played an important role, producing more hydrometeors and tuning the unbalanced moisture and temperature fields. The neighborhood-based ETS revealed that the assimilation with the specific humidity adjustment was propitious in improving forecast skill, specifically for smaller-scale reflectivity at the stage of Morakot landing, and for larger-scale reflectivity at the stage of Morakot going inland. The calculation of the intensity-scale skill score of the hourly precipitation forecast showed the assimilation with the specific humidity adjustment performed skillful forecasting for the spatial forecast-error scales of 30–160 km. Full article

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

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19 pages, 12174 KB

Open AccessEditor’s ChoiceArticle

Spatiotemporal Trends and Exceedance Drivers of Ozone Concentration in the Yangtze River Delta Urban Agglomeration, China

by Junli Xu and Jian Wang

Atmosphere 2025, 16(8), 907; https://doi.org/10.3390/atmos16080907 - 26 Jul 2025

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Abstract

The Yangtze River Delta urban agglomeration, characterized by high population density, an advanced transportation system, and a concentration of industrial activity, is one of the regions severely affected by O₃ pollution in central and eastern China. Using data collected from 251 monitoring [...] Read more.

The Yangtze River Delta urban agglomeration, characterized by high population density, an advanced transportation system, and a concentration of industrial activity, is one of the regions severely affected by O₃ pollution in central and eastern China. Using data collected from 251 monitoring stations between 2015 and 2025, this paper analyzed the spatio-temporal variation of 8 h O₃ concentrations and instances of exceedance. On the basis of exploring the influence of meteorological factors on regional 8 h O₃ concentration, the potential source contribution areas of pollutants under the exceedance condition were investigated using the HYSPLIT model. The results indicate a rapid increase in the 8 h O₃ concentration at a rate of 0.91 ± 0.98 μg·m⁻³·a⁻¹, with the average number of days exceeding concentration standards reaching 41.05 in the Yangtze River Delta urban agglomeration. Spatially, the 8 h O₃ concentrations were higher in coastal areas and lower in inland regions, as well as elevated in plains compared to hilly terrains. This distribution was significantly distinct from the concentration growth trend characterized by higher levels in the northwest and lower levels in the southeast. Furthermore, it diverged from the spatial characteristics where exceedances primarily occurred in the heavily industrialized northeastern region and the lightly industrialized central region, indicating that the growth and exceedance of 8 h O₃ concentrations were influenced by disparate factors. Local human activities have intensified the emissions of ozone precursor substances, which could be the key driving factor for the significant increase in regional 8 h O₃ concentrations. In the context of high temperatures and low humidity, this has contributed to elevated levels of 8 h O₃ concentrations. When wind speeds were below 2.5 m·s⁻¹, the proportion of 8 h O₃ concentrations exceeding the standards was nearly 0 under almost calm wind conditions, and it showed an increasing trend with rising wind speeds, indicating that the potential precursor sources that caused high O₃ concentrations originated occasionally from inland regions, with very limited presence within the study area. This observation implies that the main cause of exceedances was the transport effect of pollution from outside the region. Therefore, it is recommended that the Yangtze River Delta urban agglomeration adopt economic and technological compensation mechanisms within and between regions to reduce the emission intensity of precursor substances in potential source areas, thereby effectively controlling O₃ concentrations and improving public living conditions and quality of life. Full article

(This article belongs to the Special Issue Characteristics and Trends of Air Pollutants and Their Relationship to Atmospheric Circulations)

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29 pages, 32010 KB

Open AccessEditor’s ChoiceArticle

Assessing Environmental Sustainability in the Eastern Mediterranean Under Anthropogenic Air Pollution Risks Through Remote Sensing and Google Earth Engine Integration

by Mohannad Ali Loho, Almustafa Abd Elkader Ayek, Wafa Saleh Alkhuraiji, Safieh Eid, Nazih Y. Rebouh, Mahmoud E. Abd-Elmaboud and Youssef M. Youssef

Atmosphere 2025, 16(8), 894; https://doi.org/10.3390/atmos16080894 - 22 Jul 2025

Cited by 2 | Viewed by 1618

Abstract

Air pollution monitoring in ungauged zones presents unique challenges yet remains critical for understanding environmental health impacts and socioeconomic dynamics in the Eastern Mediterranean region. This study investigates air pollution patterns in northwestern Syria during 2019–2024, analyzing NO₂ and CO concentrations using [...] Read more.

Air pollution monitoring in ungauged zones presents unique challenges yet remains critical for understanding environmental health impacts and socioeconomic dynamics in the Eastern Mediterranean region. This study investigates air pollution patterns in northwestern Syria during 2019–2024, analyzing NO₂ and CO concentrations using Sentinel-5P TROPOMI satellite data processed through Google Earth Engine. Monthly concentration averages were examined across eight key locations using linear regression analysis to determine temporal trends, with Spearman’s rank correlation coefficients calculated between pollutant levels and five meteorological parameters (temperature, humidity, wind speed, atmospheric pressure, and precipitation) to determine the influence of political governance, economic conditions, and environmental sustainability factors on pollution dynamics. Quality assurance filtering retained only measurements with values ≥ 0.75, and statistical significance was assessed at a p < 0.05 level. The findings reveal distinctive spatiotemporal patterns that reflect the region’s complex political-economic landscape. NO₂ concentrations exhibited clear political signatures, with opposition-controlled territories showing upward trends (Al-Rai: 6.18 × 10⁻⁸ mol/m²) and weak correlations with climatic variables (<0.20), indicating consistent industrial operations. In contrast, government-controlled areas demonstrated significant downward trends (Hessia: −2.6 × 10⁻⁷ mol/m²) with stronger climate–pollutant correlations (0.30–0.45), reflecting the impact of economic sanctions on industrial activities. CO concentrations showed uniform downward trends across all locations regardless of political control. This study contributes significantly to multiple Sustainable Development Goals (SDGs), providing critical baseline data for SDG 3 (Health and Well-being), mapping urban pollution hotspots for SDG 11 (Sustainable Cities), demonstrating climate–pollution correlations for SDG 13 (Climate Action), revealing governance impacts on environmental patterns for SDG 16 (Peace and Justice), and developing transferable methodologies for SDG 17 (Partnerships). These findings underscore the importance of incorporating environmental safeguards into post-conflict reconstruction planning to ensure sustainable development. Full article

(This article belongs to the Special Issue Study of Air Pollution Based on Remote Sensing (2nd Edition))

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17 pages, 2818 KB

Open AccessEditor’s ChoiceArticle

Carbon Density Change Characteristics and Driving Factors During the Natural Succession of Forests on Xinglong Mountain in the Transition Zone Between the Qinghai–Tibet and Loess Plateaus

by Wenzhen Zong, Zhengni Chen, Quanlin Ma, Lei Ling and Yiming Zhong

Atmosphere 2025, 16(7), 890; https://doi.org/10.3390/atmos16070890 - 20 Jul 2025

Viewed by 392

Abstract

The transition zone between the Qinghai–Tibet and Loess Plateaus is an important ecological functional area and carbon (C) reservoir in China. Studying the main drivers of C density changes in forest ecosystems is crucial to enhance the C sink potential of those ecosystems [...] Read more.

The transition zone between the Qinghai–Tibet and Loess Plateaus is an important ecological functional area and carbon (C) reservoir in China. Studying the main drivers of C density changes in forest ecosystems is crucial to enhance the C sink potential of those ecosystems in ecologically fragile regions. In this study, four stand types at different succession stages in the transition zone of Xinglong Mountain were selected as the study objective. The C densities of the ecosystem, vegetation, plant debris, and soil of each stand type were estimated, and the related driving factors were quantified. The results showed that the forest ecosystem C density continuously increased significantly with natural succession (381.23 Mg/hm² to 466.88 Mg/hm²), indicating that the ecosystem has a high potential for C sequestration with progressive forest succession. The increase in ecosystem C density was mainly contributed to by the vegetation C density, which was jointly affected by the vegetation characteristics (C sink, mean diameter at breast height, mean tree height), litter C/N (nitrogen), and surface soil C/N, with factors explaining 95.1% of the variation in vegetation C density, while the net effect of vegetation characteristics was the strongest (13.9%). Overall, this study provides a new insight for understanding the C cycle mechanism in ecologically fragile areas and further improves the theoretical framework for understanding the C sink function of forest ecosystems. Full article

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

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24 pages, 50503 KB

Open AccessEditor’s ChoiceArticle

Quantifying the Influence of Sea Surface Temperature Anomalies on the Atmosphere and Precipitation in the Southwestern Atlantic Ocean and Southeastern South America

by Mylene Cabrera, Luciano Pezzi, Marcelo Santini and Celso Mendes

Atmosphere 2025, 16(7), 887; https://doi.org/10.3390/atmos16070887 - 19 Jul 2025

Viewed by 694

Abstract

Oceanic mesoscale activity influences the atmosphere in the southwestern and southern sectors of the Atlantic Ocean. However, the influence of high latitudes, specifically sea ice, on mid-latitudes and a better understanding of mesoscale ocean–atmosphere thermodynamic interactions still require further study. To quantify the [...] Read more.

Oceanic mesoscale activity influences the atmosphere in the southwestern and southern sectors of the Atlantic Ocean. However, the influence of high latitudes, specifically sea ice, on mid-latitudes and a better understanding of mesoscale ocean–atmosphere thermodynamic interactions still require further study. To quantify the effects of oceanic mesoscale activity during the periods of maximum and minimum Antarctic sea ice extent (September 2019 and February 2020), numerical experiments were conducted using a coupled regional model and an online two-dimensional spatial filter to remove high-frequency sea surface temperature (SST) oscillations. The largest SST anomalies were observed in the Brazil–Malvinas Confluence and along oceanic fronts in September, with maximum SST anomalies reaching 4.23 °C and −3.71 °C. In February, the anomalies were 2.18 °C and −3.06 °C. The influence of oceanic mesoscale activity was evident in surface atmospheric variables, with larger anomalies also observed in September. This influence led to changes in the vertical structure of the atmosphere, affecting the development of the marine atmospheric boundary layer (MABL) and influencing the free atmosphere above the MABL. Modulations in precipitation patterns were observed, not only in oceanic regions, but also in adjacent continental areas. This research provides a novel perspective on ocean–atmosphere thermodynamic coupling, highlighting the mesoscale role and importance of its representation in the study region. 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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18 pages, 6313 KB

Open AccessEditor’s ChoiceArticle

Unveiling PM_2.5 Transport Pathways: A Trajectory-Channel Model Framework for Spatiotemporally Quantitative Source Apportionment

by Yong Pan, Jie Zheng, Fangxin Fang, Fanghui Liang, Mengrong Yang, Lei Tong and Hang Xiao

Atmosphere 2025, 16(7), 883; https://doi.org/10.3390/atmos16070883 - 18 Jul 2025

Cited by 1 | Viewed by 454

Abstract

In this study, we introduced a novel Trajectory-Channel Transport Model (TCTM) to unravel spatiotemporal dynamics of PM_2.5 pollution. By integrating high-resolution simulations from the Weather Research and Forecasting (WRF) model with the Nested Air-Quality Prediction Modeling System (WRF-NAQPMS) and 72 h backward-trajectory [...] Read more.

In this study, we introduced a novel Trajectory-Channel Transport Model (TCTM) to unravel spatiotemporal dynamics of PM_2.5 pollution. By integrating high-resolution simulations from the Weather Research and Forecasting (WRF) model with the Nested Air-Quality Prediction Modeling System (WRF-NAQPMS) and 72 h backward-trajectory analysis, TCTM enables the precise identification of source regions, the delineation of key transport corridors, and a quantitative assessment of regional contributions to receptor sites. Focusing on four Yangtze River Delta cities (Hangzhou, Shanghai, Nanjing, Hefei) during a January 2020 pollution event, the results demonstrate that TCTM’s Weighted Concentration Source (WCS) and Source Pollution Characteristic Index (SPCI) outperform traditional PSCF and CWT methods in source-attribution accuracy and resolution. Unlike receptor-based statistical approaches, TCTM reconstructs pollutant transport processes, quantifies spatial decay, and assigns contributions via physically interpretable metrics. This innovative framework offers actionable insights for targeted air-quality management strategies, highlighting its potential as a robust tool for pollution mitigation planning. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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37 pages, 7235 KB

Open AccessEditor’s ChoiceArticle

New Challenges for Tropical Cyclone Track and Intensity Forecasting in an Unfavorable External Environment in the Western North Pacific—Part II: Intensifications near and North of 20° N

by Russell L. Elsberry, Hsiao-Chung Tsai, Wen-Hsin Huang and Timothy P. Marchok

Atmosphere 2025, 16(7), 879; https://doi.org/10.3390/atmos16070879 - 17 Jul 2025

Viewed by 1031

Abstract

Part I of this two-part documentation of the ECMWF ensemble (ECEPS) new tropical cyclone track and intensity forecasting challenges during the 2024 western North Pacific season described four typhoons that started well to the south of an unfavorable external environment north of 20° [...] Read more.

Part I of this two-part documentation of the ECMWF ensemble (ECEPS) new tropical cyclone track and intensity forecasting challenges during the 2024 western North Pacific season described four typhoons that started well to the south of an unfavorable external environment north of 20° N. In this Part II, five other 2024 season typhoons that formed and intensified near and north of 20° N are documented. One change is that the Cooperative Institute for Meteorological Satellite Studies ADT + AIDT intensities derived from the Himawari-9 satellite were utilized for initialization and validation of the ECEPS intensity forecasts. Our first objective of providing earlier track and intensity forecast guidance than the Joint Typhoon Warning Center (JTWC) five-day forecasts was achieved for all five typhoons, although the track forecast spread was large for the early forecasts. For Marie (06 W) and Ampil (08 W) that formed near 25° N, 140° E in the middle of the unfavorable external environment, the ECEPS intensity forecasts accurately predicted the ADT + AIDT intensities with the exception that the rapid intensification of Ampil over the Kuroshio ocean current was underpredicted. Shanshan (11 W) was a challenging forecast as it intensified to a typhoon while being quasi-stationary near 17° N, 142° E before turning to the north to cross 20° N into the unfavorable external environment. While the ECEPS provided accurate guidance as to the timing and the longitude of the 20° N crossing, the later recurvature near Japan timing was a day early and 4 degrees longitude to the east. The ECEPS provided early, accurate track forecasts of Jebi’s (19 W) threat to mainland Japan. However, the ECEPS was predicting extratropical transition with V_max ~35 kt when the JTWC was interpreting Jebi’s remnants as a tropical cyclone. The ECEPS predicted well the unusual southward track of Krathon (20 W) out of the unfavorable environment to intensify while quasi-stationary near 18.5° N, 125.6° E. However, the rapid intensification as Krathon moved westward along 20° N was underpredicted. Full article

(This article belongs to the Special Issue Typhoon/Hurricane Dynamics and Prediction (2nd Edition))

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15 pages, 3070 KB

Open AccessEditor’s ChoiceArticle

Characteristics and Sources of VOCs During a Period of High Ozone Levels in Kunming, China

by Chuantao Huang, Yufei Ling, Yunbo Chen, Lei Tong, Yuan Xue, Chunli Liu, Hang Xiao and Cenyan Huang

Atmosphere 2025, 16(7), 874; https://doi.org/10.3390/atmos16070874 - 17 Jul 2025

Viewed by 661

Abstract

The increasing levels of ozone pollution have become a significant environmental issue in urban areas worldwide. Previous studies have confirmed that the urban ozone pollution in China is mainly controlled by volatile organic compounds (VOCs) rather than nitrogen oxides. Therefore, a study on [...] Read more.

The increasing levels of ozone pollution have become a significant environmental issue in urban areas worldwide. Previous studies have confirmed that the urban ozone pollution in China is mainly controlled by volatile organic compounds (VOCs) rather than nitrogen oxides. Therefore, a study on the emission characteristics and source analysis of VOCs is important for controlling urban ozone pollution. In this study, hourly concentrations of 57 VOC species in four groups were obtained in April 2022, a period of high ozone pollution in Kunming, China. The ozone formation potential analysis showed that the accumulated reactive VOCs significantly contributed to the subsequent ozone formation, particularly aromatics (44.16%) and alkanes (32.46%). In addition, the ozone production rate in Kunming is mainly controlled by VOCs based on the results of the empirical kinetic modeling approach (K_NOx/K_VOCs = 0.25). The hybrid single-particle Lagrangian integrated trajectory model and polar coordinate diagram showed high VOC and ozone concentrations from the southwest outside the province (50.28%) and the south in local areas (12.78%). Six factors were obtained from the positive matrix factorization model: vehicle exhaust (31.80%), liquefied petroleum gas usage (24.16%), the petrochemical industry (17.81%), fuel evaporation (11.79%), coal burning (7.47%), and solvent usage (6.97%). These findings underscore that reducing anthropogenic VOC emissions and strengthening controls on the related sources could provide a scientifically robust strategy for mitigating ozone pollution in Kunming. Full article

(This article belongs to the Section Air Quality)

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18 pages, 3353 KB

Open AccessEditor’s ChoiceArticle

An Evaluation of a Novel Air Pollution Abatement System for Ammonia Emissions Reduction in a UK Livestock Building

by Andrea Pacino, Antonino La Rocca, Donata Magrin and Fabio Galatioto

Atmosphere 2025, 16(7), 869; https://doi.org/10.3390/atmos16070869 - 17 Jul 2025

Viewed by 971

Abstract

Agriculture and animal feeding operations are responsible for 87% of ammonia emissions in the UK. Controlling NH₃ concentrations below 20 ppm is crucial to preserve workers’ and livestock’s well-being. Therefore, ammonia control systems are required for maintaining adequate air quality in livestock [...] Read more.

Agriculture and animal feeding operations are responsible for 87% of ammonia emissions in the UK. Controlling NH₃ concentrations below 20 ppm is crucial to preserve workers’ and livestock’s well-being. Therefore, ammonia control systems are required for maintaining adequate air quality in livestock facilities. This study assessed the ammonia reduction efficiency of a novel air pollution abatement (APA) system used in a pig farm building. The monitoring duration was 11 weeks. The results were compared with the baseline from a previous pig cycle during the same time of year in 2023. A ventilation-controlled room was monitored during a two-phase campaign, and the actual ammonia concentrations were measured at different locations within the site and at the inlet/outlet of the APA system. A 98% ammonia reduction was achieved at the APA outlet through NH₃ absorption in tap water. Ion chromatography analyses of farm water samples revealed NH₃ concentrations of up to 530 ppm within 83 days of APA operation. Further scanning electron microscopy and energy-dispersive X-ray inspections revealed the presence of salts and organic/inorganic matter in the solid residues. This research can contribute to meeting current ammonia regulations (NECRs), also by reusing the process water as a potential nitrogen fertiliser in agriculture. Full article

(This article belongs to the Special Issue Impacts of Anthropogenic Emissions on Air Quality)

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19 pages, 2337 KB

Open AccessEditor’s ChoiceArticle

Gas–Particle Partitioning and Temporal Dynamics of Pesticides in Urban Atmosphere Adjacent to Agriculture

by Dani Khoury, Supansa Chimjarn, Olivier Delhomme and Maurice Millet

Atmosphere 2025, 16(7), 873; https://doi.org/10.3390/atmos16070873 - 17 Jul 2025

Viewed by 553

Abstract

Air pollution caused by pesticide residues is an emerging concern in urban environments influenced by nearby agricultural activities. In this study, weekly air samples were collected between May 2018 and March 2020 in Strasbourg, France, to quantify 104 pesticides in both gas and [...] Read more.

Air pollution caused by pesticide residues is an emerging concern in urban environments influenced by nearby agricultural activities. In this study, weekly air samples were collected between May 2018 and March 2020 in Strasbourg, France, to quantify 104 pesticides in both gas and particle phases using GC-MS/MS and LC-MS/MS. Herbicides and fungicides were the most frequently detected classes, appearing in 98% of both phases followed by insecticides. Key compounds such as metalaxyl-M, diphenylamine, and bifenthrin were present in over 90% of samples. Concentrations ranged from 2.5 to 63 ng m⁻³ weekly, with cumulative annual loads exceeding 1200 ng m⁻³. Gas–particle partitioning revealed that highly volatile compounds like azinphos-ethyl favored the gas phase, while less volatile ones like bifenthrin and tebuconazole partitioned >95% into particles. A third-degree polynomial regression (R² of 0.74) revealed a nonlinear relationship between Kₚ and particle-phase concentrations, highlighting a threshold above Kₚ of 0.025 beyond which compounds accumulate disproportionately in the particulate phase. Seasonal variability showed that 36% of the annual pesticide load occurred in autumn, with total airborne levels peaking near 400 ng m⁻³, while the lowest load occurred during summer. Principal component analysis identified rainfall and total suspended particles as major drivers of pesticide phase distribution. The inhalation health risk assessed yielded hazard index values < 1 × 10⁻⁷ for all population groups, suggesting negligible non-cancer risk. This study highlights the prevalence, seasonal dynamics, and partition behavior of airborne pesticides in urban air and underscores the need for regulatory attention to this overlooked exposure route. Full article

(This article belongs to the Section Air Quality)

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23 pages, 3620 KB

Open AccessEditor’s ChoiceArticle

Temperature Prediction at Street Scale During a Heat Wave Using Random Forest

by Panagiotis Gkirmpas, George Tsegas, Denise Boehnke, Christos Vlachokostas and Nicolas Moussiopoulos

Atmosphere 2025, 16(7), 877; https://doi.org/10.3390/atmos16070877 - 17 Jul 2025

Viewed by 878

Abstract

The rising frequency of heatwaves, combined with the urban heat island effect, increases the population’s exposure to high temperatures, significantly impacting the health of vulnerable groups and the overall well-being of residents. While mesoscale meteorological models can reliably forecast temperatures across urban neighbourhoods, [...] Read more.

The rising frequency of heatwaves, combined with the urban heat island effect, increases the population’s exposure to high temperatures, significantly impacting the health of vulnerable groups and the overall well-being of residents. While mesoscale meteorological models can reliably forecast temperatures across urban neighbourhoods, dense networks of in situ measurements offer more precise data at the street scale. In this work, the Random Forest technique was used to predict street-scale temperatures in the downtown area of Thessaloniki, Greece, during a prolonged heatwave in July 2021. The model was trained using data from a low-cost sensor network, meteorological fields calculated by the mesoscale model MEMO, and micro-environmental spatial features. The results show that, although the MEMO temperature predictions achieve high accuracy during nighttime compared to measurements, they exhibit inconsistent trends across sensor locations during daytime, indicating that the model does not fully account for microclimatic phenomena. Additionally, by using only the observed temperature as the target of the Random Forest model, higher accuracy is achieved, but spatial features are not represented in the predictions. In contrast, the most reliable approach to incorporating spatial characteristics is to use the difference between observed and mesoscale temperatures as the target variable. Full article

(This article belongs to the Special Issue Urban Heat Islands, Global Warming and Effects)

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16 pages, 19476 KB

Open AccessEditor’s ChoiceArticle

Photochemical Ozone Production Along Flight Trajectories in the Upper Troposphere and Lower Stratosphere and Route Optimisation

by Allan W. Foster, Richard G. Derwent, M. Anwar H. Khan, Dudley E. Shallcross, Mark H. Lowenberg and Rukshan Navaratne

Atmosphere 2025, 16(7), 858; https://doi.org/10.3390/atmos16070858 - 14 Jul 2025

Viewed by 477

Abstract

Aviation is widely recognised to have global-scale climate impacts through the formation of ozone (O₃) in the upper troposphere and lower stratosphere (UTLS), driven by emissions of nitrogen oxides (NO_X). Ozone is known to be one of the most [...] Read more.

Aviation is widely recognised to have global-scale climate impacts through the formation of ozone (O₃) in the upper troposphere and lower stratosphere (UTLS), driven by emissions of nitrogen oxides (NO_X). Ozone is known to be one of the most potent greenhouse gases formed from the interaction of aircraft emission plumes with atmospheric species. This paper follows up on previous research, where a Photochemical Trajectory Model was shown to be a robust measure of ozone formation along flight trajectories post-flight. We use a combination of a global Lagrangian chemistry-transport model and a box model to quantify the impacts of aircraft NO_X on UTLS ozone over a five-day timescale. This work expands on the spatial and temporal range, as well as the chemical accuracy reported previously, with a greater range of NO_X chemistry relevant chemical species. Based on these models, route optimisation has been investigated, through the use of network theory and algorithms. This is to show the potential inclusion of an understanding of climate-sensitive regions of the atmosphere on route planning can have on aviation’s impact on Earth’s Thermal Radiation balance with existing resources and technology. Optimised flight trajectories indicated reductions in O₃ formation per unit NO_X are in the range 1–40% depending on the spatial aspect of the flight. Temporally, local winter times and equatorial regions are generally found to have the most significant O₃ formation per unit NO_X; moreover, hotspots were found over the Pacific and Indian Ocean. Full article

(This article belongs to the Section Air Pollution Control)

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19 pages, 3047 KB

Open AccessEditor’s ChoiceArticle

Identifying the Combined Impacts of Sensor Quantity and Location Distribution on Source Inversion Optimization

by Shushuai Mao, Jianlei Lang, Feng Hu, Xiaoqi Wang, Kai Wang, Guiqin Zhang, Feiyong Chen, Tian Chen and Shuiyuan Cheng

Atmosphere 2025, 16(7), 850; https://doi.org/10.3390/atmos16070850 - 12 Jul 2025

Viewed by 292

Abstract

Source inversion optimization using sensor observations is a key method for rapidly and accurately identifying unknown source parameters (source strength and location) in abrupt hazardous gas leaks. Sensor number and location distribution both play important roles in source inversion; however, their combined impacts [...] Read more.

Source inversion optimization using sensor observations is a key method for rapidly and accurately identifying unknown source parameters (source strength and location) in abrupt hazardous gas leaks. Sensor number and location distribution both play important roles in source inversion; however, their combined impacts on source inversion optimization remain poorly understood. In our study, the optimization inversion method is established based on the Gaussian plume model and the generation algorithm. A research strategy combining random sampling and coefficient of variation methods was proposed to simultaneously quantify their combined impacts in the case of a single emission source. The sensor layout impact difference was analyzed under varying atmospheric conditions (unstable, neutral, and stable) and source location information (known or unknown) using the Prairie Grass experiments. The results indicated that adding sensors improved the source strength estimation accuracy more when the source location was known than when it was unknown. The impacts of sensor location distribution were strongly negatively correlated (r ≤ −0.985) with the number of sensors across scenarios. For source strength estimation, the impacts of the sensor location distribution difference decreased non-linearly with more sensors for known locations but linearly for unknown ones. The impacts of sensor number and location distribution on source strength estimation were amplified under stable atmospheric conditions compared to unstable and neutral conditions. The minimum number of randomly scattered sensors required for stable source strength inversion accuracy was 11, 12, and 17 for known locations under unstable, neutral, and stable atmospheric conditions, respectively, and 24, 9, and 21 for unknown locations. The multi-layer arc distribution outperformed rectangular, single-layer arc, and downwind-axis distributions in source strength estimation. This study enhances the understanding of factors influencing source inversion optimization and provides valuable insights for optimizing sensor layouts. Full article

(This article belongs to the Section Air Pollution Control)

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23 pages, 3967 KB

Open AccessEditor’s ChoiceArticle

Comparative Analysis of Machine Learning Algorithms for Potential Evapotranspiration Estimation Using Limited Data at a High-Altitude Mediterranean Forest

by Stefanos Stefanidis, Konstantinos Ioannou, Nikolaos Proutsos, Ilias Karmiris and Panagiotis Stefanidis

Atmosphere 2025, 16(7), 851; https://doi.org/10.3390/atmos16070851 - 12 Jul 2025

Viewed by 689

Abstract

Accurate estimation of potential evapotranspiration (PET) is of paramount importance for water resource management, especially in Mediterranean mountainous environments that are often data-scarce and highly sensitive to climate variability. This study evaluates the performance of four machine learning (ML) regression algorithms—Support Vector Regression [...] Read more.

Accurate estimation of potential evapotranspiration (PET) is of paramount importance for water resource management, especially in Mediterranean mountainous environments that are often data-scarce and highly sensitive to climate variability. This study evaluates the performance of four machine learning (ML) regression algorithms—Support Vector Regression (SVR), Random Forest Regression (RFR), Gradient Boosting Regression (GBR), and K-Nearest Neighbors (KNN)—in predicting daily PET using limited meteorological data from a high-altitude in Central Greece. The ML models were trained and tested using easily available meteorological inputs—temperature, relative humidity, and extraterrestrial solar radiation—on a dataset covering 11 years (2012–2023). Among the tested configurations, RFR showed the best performance (R² = 0.917, RMSE = 0.468 mm/d, MAPE = 0.119 mm/d) when all the above-mentioned input variables were included, closely approximating FAO56–PM outputs. Results bring to light the potential of machine learning models to reliably estimate PET in data-scarce conditions, with RFR outperforming others, whereas the inclusion of the easily estimated extraterrestrial radiation parameter in the ML models training enhances PET prediction accuracy. Full article

(This article belongs to the Special Issue Observation and Modeling of Evapotranspiration)

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