Atmosphere

16 pages, 6912 KiB

Open AccessArticle

The Interannual Cyclicity of Precipitation in Xinjiang During the Past 70 Years and Its Contributing Factors

by Wenjie Ma, Xiaokang Liu, Shasha Shang, Zhen Wang, Yuyang Sun, Jian Huang, Mengfei Ma, Meihong Ma and Liangcheng Tan

Atmosphere 2025, 16(5), 629; https://doi.org/10.3390/atmos16050629 (registering DOI) - 21 May 2025

Abstract

Precipitation cyclicity plays a crucial role in regional water supply and climate predictions. In this study, we used observational data from 34 representative meteorological stations in the Xinjiang region, a major part of inland arid China, to characterize the interannual cyclicity of regional [...] Read more.

Precipitation cyclicity plays a crucial role in regional water supply and climate predictions. In this study, we used observational data from 34 representative meteorological stations in the Xinjiang region, a major part of inland arid China, to characterize the interannual cyclicity of regional precipitation from 1951 to 2021 and analyze its contributing factors. The results indicated that the mean annual precipitation in Xinjiang (MAP_XJ) was dominated by a remarkably increasing trend over the past 70 years, which was superimposed by two bands of interannual cycles of approximately 3 years with explanatory variance of 56.57% (Band I) and 6–7 years with explanatory variance of 23.38% (Band II). This is generally consistent with previous studies on the cyclicity of precipitation in Xinjiang for both seasonal and annual precipitation. We analyzed the North Tropical Atlantic sea-surface temperature (NTA_SST), El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Arctic Oscillation (AO), and Indian Summer Monsoon (ISM) as potential forcing factors that show similar interannual cycles and may contribute to the identified precipitation variability. Two approaches, multivariate linear regression and the Random Forest model, were employed to ascertain the relative significance of each factor influencing Bands I and II, respectively. The multivariate linear regression analysis revealed that the AO index contributed the most to Band I, with a significance score of −0.656, whereas the ENSO index with a one-year lead (ENSO_−1yr) played a dominant role in Band II (significance score = 0.457). The Random Forest model also suggested that the AO index exhibited the highest significance score (0.859) for Band I, whereas the AO index with a one-year lead (AO_−1yr) had the highest significance score (0.876) for Band II. Overall, our findings highlight the necessity of employing different methods that consider both the linear and non-linear response of climate variability to driving factors crucial for future climate prediction. Full article

(This article belongs to the Special Issue Desert Climate and Environmental Change: From Past to Present)

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14 pages, 6252 KiB

Open AccessArticle

Influence of Satellite and Presatellite Periods on the Validation of Major Sudden Stratospheric Warmings in Historical CMIP5 Simulations

by Víctor Manuel Chávez-Pérez, Juan Antonio Añel-Cabanelas, Citlalli Almaguer-Gómez and Laura de la Torre-Ramos

Atmosphere 2025, 16(5), 628; https://doi.org/10.3390/atmos16050628 - 21 May 2025

Abstract

This study assesses the ability of fourteen CMIP5 climate models to reproduce the main characteristics of major stratospheric sudden warmings (SSWp) in historical simulations. Model performance is evaluated through comparisons with three reanalysis datasets, considering two periods: the satellite era (1979–2005) and an [...] Read more.

This study assesses the ability of fourteen CMIP5 climate models to reproduce the main characteristics of major stratospheric sudden warmings (SSWp) in historical simulations. Model performance is evaluated through comparisons with three reanalysis datasets, considering two periods: the satellite era (1979–2005) and an extended period including pre-satellite years (1958–2005). Results show that model consistency with reanalyses is significantly higher during the satellite period, with up to seven models showing no statistically significant differences (p > 0.05) in at least eight out of ten key diagnostics. In contrast, performance decreases in the extended period, likely due to greater observational uncertainty. A systematic overrepresentation of displacement-type events (SSW_D) was found in most models, compared to the split-type dominance in reanalysis data. These findings highlight the importance of the validation period and event classification in model evaluation and establish a robust framework for future comparisons using CMIP6 models and newer reanalysis products. Full article

(This article belongs to the Section Climatology)

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26 pages, 31123 KiB

Open AccessArticle

Drivers of a Summertime Combined High Air Pollution Event of Ozone and PM_2.5 in Taiyuan, China

by Jiangpeng Miao, Yuxi Wang, Liqiang Xu, Hongyi Ding, Simeng Li, Luhang Sun and Le Cao

Atmosphere 2025, 16(5), 627; https://doi.org/10.3390/atmos16050627 - 20 May 2025

Abstract

Combined air pollution of ozone and PM_2.5 often occurs in coal-based cities of China such as Taiyuan City. In this study, the Weather Research and Forecasting/Chemistry (WRF-Chem) model was employed to simulate a combined high air pollution event of ozone and PM [...] Read more.

Combined air pollution of ozone and PM_2.5 often occurs in coal-based cities of China such as Taiyuan City. In this study, the Weather Research and Forecasting/Chemistry (WRF-Chem) model was employed to simulate a combined high air pollution event of ozone and PM_2.5 in Taiyuan City from 20 May to 29 May 2015,with the maximum daily 8-hour average (MDA8) for ozone exceeding 140 ppbv and PM_2.5 concentrations surpassing

200 µ g m^{- 3}

. We further investigated the drivers of the combined air pollution in Taiyuan during the polluted period. The simulation results showed that the model can well simulate the combined pollution event in Taiyuan, with assessment parameters within reasonable ranges. Moreover, by analyzing the observational data and simulations, the major factors causing the PM_2.5 pollution in Taiyuan during this time period were suggested to be local emissions and pollutant transport from the North China Plain (NCP) located to the east of Taiyuan. In addition, unfavorable meteorological and geographical conditions in Taiyuan also play important roles in forming severe PM_2.5 pollution. Regarding the ozone pollution in Taiyuan, we suggest that the mechanism dominating the pollution event is that of ozone-rich air being transported to Taiyuan at high altitudes and then mixed downwards, resulting in an increase of the ground-level ozone in Taiyuan. Furthermore, we found local emissions and emissions from Taiyuan Basin and Henan Province, which are located to the south of Taiyuan, contributing significantly to the ozone pollution in Taiyuan City during this time. Full article

(This article belongs to the Section Air Quality)

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20 pages, 810 KiB

Open AccessReview

A Review of Offshore Methane Quantification Methodologies

by Stuart N. Riddick, Mercy Mbua, Catherine Laughery and Daniel J. Zimmerle

Atmosphere 2025, 16(5), 626; https://doi.org/10.3390/atmos16050626 - 20 May 2025

Abstract

Since pre-industrial times, anthropogenic methane emissions have increased and are partly responsible for a changing global climate. Natural gas and oil extraction activities are one significant source of anthropogenic methane. While methods have been developed and refined to quantify onshore methane emissions, the [...] Read more.

Since pre-industrial times, anthropogenic methane emissions have increased and are partly responsible for a changing global climate. Natural gas and oil extraction activities are one significant source of anthropogenic methane. While methods have been developed and refined to quantify onshore methane emissions, the ability of methods to directly quantify emissions from offshore production facilities remains largely unknown. Here, we review recent studies that have directly measured emissions from offshore production facilities and critically evaluate the suitability of these measurement strategies for emission quantification in a marine environment. The average methane emissions from production platforms measured using downwind dispersion methods were 32 kg h⁻¹ from 188 platforms; 118 kg h⁻¹ from 104 platforms using mass balance methods; 284 kg h⁻¹ from 151 platforms using aircraft remote sensing; and 19,088 kg h⁻¹ from 10 platforms using satellite remote sensing. Upon review of the methods, we suggest the unusually large emissions, or zero emissions observed could be caused by the effects of a decoupling of the marine boundary layer (MBL). Decoupling can happen when the MBL becomes too deep or when there is cloud cover and results in a stratified MBL with air layers of different depths moving at different speeds. Decoupling could cause: some aircraft remote sensing observations to be biased high (lower wind speed at the height of the plume); the mass balance measurements to be biased high (narrow plume being extrapolated too far vertically) or low (transects miss the plume); and the downwind dispersion measurements much lower than the other methods or zero (plume lofting in a decoupled section of the boundary layer). To date, there has been little research on the marine boundary layer, and guidance on when decoupling happens is not currently available. We suggest an offshore controlled release program could provide a better understanding of these results by explaining how and when stratification happens in the MBL and how this affects quantification methodologies. Full article

(This article belongs to the Section Air Quality)

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14 pages, 1291 KiB

Open AccessArticle

Short-Term Ozone Exposure and Daily Mortality in Suburban and Rural Areas of Southern Europe

by Maria Angela Doronzo, José Ramón Martinez Fernandez, Diana Gómez-Barroso, María Alonso-Colón, Beatriz Nuñez-Corcuera and Rebeca Ramis

Atmosphere 2025, 16(5), 625; https://doi.org/10.3390/atmos16050625 - 20 May 2025

Abstract

Ozone (O₃) is a major air pollutant with significant health effects, including increased respiratory and cardiovascular mortality. While previous research has largely focused on urban areas, this study assesses the association between maximum 8 h O₃ concentrations and non-accidental mortality, [...] Read more.

Ozone (O₃) is a major air pollutant with significant health effects, including increased respiratory and cardiovascular mortality. While previous research has largely focused on urban areas, this study assesses the association between maximum 8 h O₃ concentrations and non-accidental mortality, including cardiovascular and respiratory mortality, in suburban and rural areas of Spain. We conducted a nationwide time-series analysis across 122 municipalities between April and September 2017 using Poisson regression models and adjusting for daily maximum temperature and provincial variability. Distributed lag models were applied to estimate the cumulative effects of ozone exposure on mortality, considering lags from 1 to 30 days. For each 10 µg/m³ increase in 8 h maximum O₃ concentration, a significant increase in all-cause mortality risk of 2.3% was observed, with a peak at lag 2. Cardiovascular mortality increased by 2.4%, also peaking at lag 2, while respiratory mortality showed the strongest association, with a 4.3% rise at lag 1. A secondary mortality risk increase was observed at lags 24–28, suggesting the potential delayed effects of O₃ exposure. These findings showed higher risk than those previously reported for urban populations and highlight the need for targeted public health interventions to mitigate the impact of ozone pollution in non-urban populations. Full article

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

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14 pages, 1814 KiB

Open AccessArticle

Atmospheric Photochemical Oxidation of 4-Nitroimidazole

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

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

Abstract

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

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

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

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12 pages, 959 KiB

Open AccessArticle

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

by Natallia Miatselskaya, Andrey Bril and Anatoly Chaikovsky

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

Abstract

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

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

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

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21 pages, 8687 KiB

Open AccessArticle

Assessment of Coastal Zone Vulnerability in Context of Sea-Level Rise and Inundation Risk in Qatar

by Abdulaziz Ali M. Al-Mannai, Sarra Ouerghi and Mohamed Elhag

Atmosphere 2025, 16(5), 622; https://doi.org/10.3390/atmos16050622 - 19 May 2025

Abstract

Coastal zones represent the most active interfaces where natural processes and human activities converge, making them crucial for biodiversity and socioeconomic development. These zones are characterized by their fragility and susceptibility to frequent natural disasters, such as floods and erosion, which are exacerbated [...] Read more.

Coastal zones represent the most active interfaces where natural processes and human activities converge, making them crucial for biodiversity and socioeconomic development. These zones are characterized by their fragility and susceptibility to frequent natural disasters, such as floods and erosion, which are exacerbated by high-intensity human activities and urban expansion. The ongoing challenges posed by rising sea levels and climate change necessitate robust scientific assessments of coastal vulnerability to ensure effective disaster prevention and environmental protection. This paper introduces a comprehensive evaluation system for assessing coastal zone vulnerability, utilizing multi-source data to address ecological vulnerabilities stemming from sea-level rise and climate change impacts. This system is applied to examine the specific case of Qatar, where rapid urban development and a high population density in coastal areas heighten the risk of flooding and inundation. Employing remote sensing data and Geographic Information Systems (GISs), this research leverages spatial interpolation techniques and high-resolution digital elevation models (DEMs) to identify and evaluate high-risk zones susceptible to sea-level rise. In this study, the hydrological connectivity model, bathtub technique, and CVI are interconnected tools that complement each other to assess future flooding risks under various climate change projections, highlighting the increased probability of coastal hazards. The findings underscore the urgent need for adaptive planning and regulatory frameworks to mitigate these risks, providing technical support for the sustainable development of coastal communities globally and in Qatar. This approach not only informs policy makers, but also aids in the strategic planning required to foster resilient coastal infrastructure capable of withstanding both current and future environmental challenges. Full article

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

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21 pages, 9316 KiB

Open AccessArticle

Estimation of High Spatial Resolution CO₂ Concentration in China from 2010 to 2022 Based on Multi-Source Carbon Satellite Data

by Shanzhao Cai, Heng Dong, Bo Zhang and Huan Huang

Atmosphere 2025, 16(5), 621; https://doi.org/10.3390/atmos16050621 - 19 May 2025

Viewed by 120

Abstract

The increase in the carbon dioxide (CO₂) concentration is a major driver of global warming, presenting significant challenges to ecosystems and human societies. Satellite remote sensing technology can monitor the continuous spatial variation of the atmospheric CO₂ column concentration (XCO [...] Read more.

The increase in the carbon dioxide (CO₂) concentration is a major driver of global warming, presenting significant challenges to ecosystems and human societies. Satellite remote sensing technology can monitor the continuous spatial variation of the atmospheric CO₂ column concentration (XCO₂), but its global application is limited by the narrow observational swath. To address this, this study effectively integrates XCO₂ data retrieved from the GOSAT and OCO-2 satellites using atmospheric profile adjustment and spatial grid integration techniques. Based on this, a multi-machine learning ensemble algorithm (MLE) was developed, which successfully estimated the spatially continuous XCO₂ concentration in China from 2010 to 2022 (ChinaXCO₂-MLE). The results indicate that, compared to individual satellite observations, the integration of multi-source satellite XCO₂ data significantly improves the spatiotemporal coverage. The overall R² of the MLE model was 0.97, with an RMSE of 0.87 ppmv, outperforming single machine learning models. The ChinaXCO₂-MLE shows good consistency with the observational records from two background stations in China, with R² values of 0.93 and 0.78, and corresponding RMSEs of 1.00 ppmv and 1.32 ppmv. This study also reveals the seasonal and regional variations in China’s XCO₂ concentration: the highest concentration occurs in spring, the lowest concentration occurs in northern regions during summer, and the lowest concentration occurs in southern regions during autumn. From 2010 to 2022, the XCO₂ concentration continued to rise, but the growth rate has slowed due to the implementation of air pollution prevention and energy conservation policies. The spatially continuous XCO₂ data provide a more comprehensive understanding of carbon variation and offer a valuable reference for achieving China’s carbon neutrality goals. Full article

(This article belongs to the Section Air Quality)

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17 pages, 3126 KiB

Open AccessArticle

Investigating the Sensitivity of Modelled Ozone Levels in the Mediterranean to Dry Deposition Parameters

by André Barreirinha, Sabine Banzhaf, Markus Thürkow, Carla Gama, Michael Russo, Enrico Dammers, Martijn Schaap and Alexandra Monteiro

Atmosphere 2025, 16(5), 620; https://doi.org/10.3390/atmos16050620 - 19 May 2025

Viewed by 134

Abstract

The exposure to elevated levels of ozone contributes to respiratory diseases and ecosystem degradation. Mediterranean countries are among those most affected by high ozone concentrations, which are generally overestimated by chemistry transport models underscoring the importance of improving the accuracy of air quality [...] Read more.

The exposure to elevated levels of ozone contributes to respiratory diseases and ecosystem degradation. Mediterranean countries are among those most affected by high ozone concentrations, which are generally overestimated by chemistry transport models underscoring the importance of improving the accuracy of air quality modelling. This study introduces an enhanced Mediterranean dry deposition description within the LOTOS-EUROS model framework, focusing on refining key vegetation parameters for the Mediterranean climate zone, with the goal to better estimate deposition and connected concentration values. Adjustments were made to the vegetation type dependent Jarvis functions for temperature and vapour pressure deficit, as well as to the maximum stomatal conductance across four land use types: arable land, crops, deciduous broadleaf forest, and coniferous evergreen forest. The model’s baseline run showed a widespread overestimation of ozone. Adjustments to the dry deposition routines reduced this overestimation, but the model simulation incorporating all changes still showed elevated ozone levels. Both runs displayed moderate spatial correlation with observations from 117 rural background monitoring stations, and most stations exhibited a temporal correlation between 0.5 and 0.8. An improved RMSE and bias were noted at the majority of the stations (114 out of 117) for the model simulation incorporating all changes. The monthly analysis indicated consistent overestimation at two Portuguese sites beginning in March. The model effectively tracked temporal changes overall. However, the diurnal analysis revealed site-specific differences: an overestimation at the station closest to highly populated areas at night, while rural stations aligned better with observed values. These results highlight the benefits of region-specific model adaptations and lay the groundwork for further advancements, such as incorporating detailed vegetation classifications and seasonal variations. Full article

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

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16 pages, 11579 KiB

Open AccessArticle

Characteristic Analysis of the Extreme Precipitation over South China During the Dragon-Boat Precipitation in 2022

by Meixia Chen, Yufeng Xue, Juliao Qiu, Chunlei Liu, Shuqin Zhang, Jianjun Xu and Ziye Zhu

Atmosphere 2025, 16(5), 619; https://doi.org/10.3390/atmos16050619 - 19 May 2025

Viewed by 107

Abstract

Using multi-source precipitation datasets including NASA GPM (IMERG), GPCP, ECMWF ERA5, and station precipitation data from the China Meteorological Administration (CMA), along with ERA5 reanalysis fields for atmospheric circulation analysis, this study investigates the extreme precipitation events during the “Dragon-Boat Precipitation” period from [...] Read more.

Using multi-source precipitation datasets including NASA GPM (IMERG), GPCP, ECMWF ERA5, and station precipitation data from the China Meteorological Administration (CMA), along with ERA5 reanalysis fields for atmospheric circulation analysis, this study investigates the extreme precipitation events during the “Dragon-Boat Precipitation” period from 20 May to 21 June over South China in 2022 using the synoptic diagnostic method. The results indicate that the total precipitation during this period significantly exceeded the climatological average, with multiple large-scale extreme rainfall events characterized by high intensity, extensive coverage, and prolonged duration. The spatial distribution of precipitation exhibited a north-more-south-less pattern, with the maximum rainfall center located in the Nanling Mountains, particularly in the Shaoguan–Qingyuan–Heyuan region of Guangdong Province, where peak precipitation exceeded 1100 mm, and the mean precipitation was approximately 1.7 times the climatology from the GPM data. The average daily precipitation throughout the period was 17.5 mm/day, which was 6 mm/day higher than the climatological mean, while the heaviest rainfall on 13 June reached 39 mm/day above the average, exceeding two standard deviations. The extreme precipitation during the “Dragon-Boat Precipitation” period in 2022 was associated with an anomalous deep East Asian trough, an intensified South Asian High, a stronger-than-usual Western Pacific Subtropical High, an enhanced South Asian monsoon and South China Sea monsoon, and the dominance of a strong Southwesterly Low-Level Jet (SLLJ) over South China. Two major moisture transport pathways were established: one from the Bay of Bengal to South China and another from the South China Sea, with the latter contributing a little higher amount of water vapor transport than the former. The widespread extreme precipitation on 13 June 2022 was triggered by the anomalous atmospheric circulation conditions. In the upper levels, South China was located at the northwestern periphery of the slightly stronger-than-normal Western Pacific Subtropical High, intersecting with the base of a deep trough associated with an anomalous intense Northeast China Cold Vortex (NCCV). At lower levels, the region was positioned along a shear line formed by anomalous southwesterly and northerly winds, where exceptionally strong southwesterly moisture transport, significant moisture convergence, and intense vertical updraft led to the widespread extreme rainfall event on that day. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks (2nd Edition))

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13 pages, 589 KiB

Open AccessArticle

The Risk of Developing Tinnitus and Air Pollution Exposure

by Po-Yu Lai, Chang-Yin Lee, Kuang-Hsi Chang, Yu-Kang Chang, Yi-Chao Hsu, Ing-Ming Chiu, Stella Chin-Shaw Tsai, Der-Yang Cho, Cheng-Li Lin, Tsung-Hsing Lin and Wu-Lung Chuang

Atmosphere 2025, 16(5), 618; https://doi.org/10.3390/atmos16050618 - 19 May 2025

Viewed by 147

Abstract

(1) Background: The role of air pollutants as risk factors for tinnitus remains unclear. To address this gap in research, we conducted a nationwide retrospective cohort study in Taiwan by integrating patients’ clinical data with daily air quality data to evaluate the environmental [...] Read more.

(1) Background: The role of air pollutants as risk factors for tinnitus remains unclear. To address this gap in research, we conducted a nationwide retrospective cohort study in Taiwan by integrating patients’ clinical data with daily air quality data to evaluate the environmental risk factors associated with tinnitus. (2) Methods: The Taiwan National Health Research Database (NHIRD) includes medical records for nearly all residents of Taiwan. To assess pollution levels, we used daily air quality data from the Taiwan Environmental Protection Agency regarding SO₂, CO, NO, NO_X, and particulate matter (PM_2.5 and PM₁₀). We merged the NHIRD data with air quality information based on the residents’ locations and the positions of air quality monitoring stations. Pollutant levels were then categorized into quartiles (Q1, Q2, Q3, and Q4). (3) Results: This study included 284,318 subjects. After controlling for covariates, the adjusted HR (95 CI%) for tinnitus increased with increasing SO₂, CO, NO, NO_X, PM_2.5, and PM₁₀ exposure levels, specifically from 1.24 (95 CI% = 1.18, 1.30) to 1.35 (95 CI% = 1.28–1.41); from 1.15 (95 CI% = 1.09, 1.21) to 1.90 (95 CI% = 1.81, 2.00); from 0.86 (95 CI% = 0.82, 0.91) to 1.69 (95 CI% = 1.62, 1.77); from 1.62 (95 CI% = 1.54, 1.71) to 1.69 (95 CI% = 1.60, 1.77); from 0.16 (95 CI% = 0.15, 0.18) to 2.70 (95 CI% = 2.57, 2.84); and from 2.53 (95 CI% = 2.38, 2.69) to 3.58 (95 CI% = 3.39, 3.78), respectively, compared to the Q1 concentrations for all air pollutants. (4) Conclusions: During the 15-year follow-up period, we found a significant positive correlation between air pollutant exposure and the risk of tinnitus. Full article

(This article belongs to the Special Issue Air Pollution Exposure and Health Impact Assessment (3rd Edition))

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24 pages, 15683 KiB

Open AccessArticle

Research on the Mechanism of the Impact of Green View Index of Urban Streets on Thermal Environment: A Machine Learning-Driven Empirical Study in Hangzhou, China

by Qiguan Wang, Yanjun Hu and Hai Yan

Atmosphere 2025, 16(5), 617; https://doi.org/10.3390/atmos16050617 - 19 May 2025

Viewed by 139

Abstract

This study investigates the relationship between Green View Index (GVI) and street thermal environment in Hangzhou’s main urban area during summer, quantifying urban greenery’s impact on diurnal/nocturnal thermal conditions to inform urban heat island mitigation strategies. Multi-source data (3D morphological metrics, LCZ classifications, [...] Read more.

This study investigates the relationship between Green View Index (GVI) and street thermal environment in Hangzhou’s main urban area during summer, quantifying urban greenery’s impact on diurnal/nocturnal thermal conditions to inform urban heat island mitigation strategies. Multi-source data (3D morphological metrics, LCZ classifications, mobile measurements) were integrated with deep learning-derived street-level GVI through image analysis. A random forest-multiple regression hybrid model evaluated spatiotemporal variations and GVI impacts across time, street orientation, and urban-rural gradients. Key findings include: (1) Urban street Ta prediction model: Daytime model: R² = 0.54, RMSE = 0.33 °C; Nighttime model: R² = 0.71, RMSE = 0.42 °C. (2) GVI shows significant inverse association with temperature, A 0.1 unit increase in GVI reduced temperatures by 0.124°C during the day and 0.020 °C at night. (3) Orientation effects: North–south streets exhibit strongest cooling (1.85 °C daytime reduction), followed by east–west; northeast–southwest layouts show negligible impact; (4) Canyon geometry: Low-aspect canyons (H/W < 1) enhance cooling efficiency, while high-aspect canyons (H/W > 2) retain nocturnal heat despite daytime cooling; (5) Urban-rural gradient: Cooling peaks in urban-fringe zones (10–15 km daytime, 15–20 km nighttime), contrasting with persistent nocturnal warmth in urban cores (0–5 km); (6) LCZ variability: Daytime cooling intensity peaks in LCZ3, nighttime in LCZ6. These findings offer scientific evidence and empirical support for urban thermal environment optimization strategies in urban planning and landscape design. We recommend dynamic coupling of street orientation, three-dimensional morphological characteristics, and vegetation configuration parameters to formulate differentiated thermal environment design guidelines, enabling precise alignment between mitigation measures and spatial context-specific features. Full article

(This article belongs to the Section Biometeorology and Bioclimatology)

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22 pages, 2255 KiB

Open AccessArticle

Homogenization of the Probability Distribution of Climatic Time Series: A Novel Algorithm

by Peter Domonkos

Atmosphere 2025, 16(5), 616; https://doi.org/10.3390/atmos16050616 - 18 May 2025

Viewed by 198

Abstract

The aim of the homogenization of climatic time series is to remove non-climatic biases from the observed data, which are caused by technical or environmental changes during the period of observations. This bias removal is generally more successful for long-term trends and annual [...] Read more.

The aim of the homogenization of climatic time series is to remove non-climatic biases from the observed data, which are caused by technical or environmental changes during the period of observations. This bias removal is generally more successful for long-term trends and annual means than for monthly and daily values. The homogenization of probability distribution (HPD) may improve data accuracy even for daily data when the signal-to-noise ratio favors its application. HPD can be performed by quantile matching or spatial interpolations, but both of them have drawbacks. This study presents a new algorithm which helps to increase homogenization accuracy in all temporal and spatial scales. The new method is similar to quantile matching, but section mean values of the probability distribution function (PDF) are compared instead of individual daily values. The input dataset of the algorithm is identical with the homogenization results for section means of the studied time series. The algorithm decides about statistical significance for each break detected during the homogenization of the section means, and skips the insignificant breaks. Correction terms for removing the inhomogeneity biases of PDF are calculated jointly by a Benova-like equation system, a low pass filter is used for smoothing the prime results, and the mean value of the input time series between two consecutive detected breaks is preserved for each of such sections. This initial version does not deal with seasonal variations either during HPD or in other steps of the homogenization. The method has been tested connecting HPD to ACMANTv5.3, and using overall 8 wind speed and relative humidity datasets of the benchmark of European project INDECIS. The results show 4 to 12 percent RMSE reduction by HPD in all temporal scales, except for the extreme tails where a part of the results are weaker. Full article

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

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8 pages, 1943 KiB

Open AccessArticle

A Forgotten Aurora: Revisiting the 19 March 1950 Aurora Australis Through Historical Records

by Víctor M. S. Carrasco and José M. Vaquero

Atmosphere 2025, 16(5), 615; https://doi.org/10.3390/atmos16050615 - 18 May 2025

Viewed by 91

Abstract

This study investigates the aurora australis event of 19 March 1950, which was reported across multiple locations in Australia, including Hobart, Sydney, and as far north as Goondiwindi. Despite its significance as a historical space weather event, this aurora has received little attention [...] Read more.

This study investigates the aurora australis event of 19 March 1950, which was reported across multiple locations in Australia, including Hobart, Sydney, and as far north as Goondiwindi. Despite its significance as a historical space weather event, this aurora has received little attention in the scientific literature. Using contemporary news reports from The Sydney Morning Herald and Mercury, we reconstruct the characteristics of the event. Observers described vivid red and green auroral displays with streamers, indicative of intense geomagnetic activity. The associated geomagnetic storm reached a Kp index of 7+. We have estimated the magnetic disturbance peak of −278 nT (±15 nT) from measurements made in the Kakioka Magnetic Observatory. This would place it among the top 50 most intense storms recorded since 1957, according to the Dst index, though still significantly below the most extreme events. Notably, this aurora is absent from modern auroral catalogs, and no documented observations from the Northern Hemisphere have been identified. These findings underscore the critical role of historical records in advancing our understanding of auroral phenomena and their relationship with solar activity. Given the provisional nature of this study, further historical documents may yet emerge, providing additional insights into this event and its broader space weather context. Full article

(This article belongs to the Special Issue Research and Space-Based Exploration on Space Plasma)

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20 pages, 95230 KiB

Open AccessArticle

Influence of Building-Height Variability on Urban Ventilation and Pollutant Dispersion Characteristics

by Taotao Shui, Lili Cao, Tieqiao Xiao and Shaojie Zhang

Atmosphere 2025, 16(5), 614; https://doi.org/10.3390/atmos16050614 - 17 May 2025

Viewed by 181

Abstract

Urban densification associated with rapid urbanization has weakened horizontal ventilation in cities. Previous studies point out that building-height variability can enhance vertical ventilation, while most of them rely on idealized models that overlook the complexity of real urban environments. This study analyzes 20 [...] Read more.

Urban densification associated with rapid urbanization has weakened horizontal ventilation in cities. Previous studies point out that building-height variability can enhance vertical ventilation, while most of them rely on idealized models that overlook the complexity of real urban environments. This study analyzes 20 actual urban blocks using CFD simulations, considering average building height, building density, and height standard deviation. The results show that areas with low-rise, uniform buildings exhibit superior pollutant dispersion, while mid- and high-rise zones experience complex turbulence and pollutant accumulation. Ventilation performance peaks when the height standard deviation ranges between 35 and 40. These findings underscore that optimizing urban form for vertical ventilation requires a combined strategy of density control and height variation. Realistic building group models more accurately capture airflow dynamics and provide valuable insights for the design of effective vertical ventilation corridors and the enhancement of urban pollutant dispersion. Full article

(This article belongs to the Section Air Quality)

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20 pages, 2025 KiB

Open AccessArticle

A Monitoring and Sampling Platform for Air Pollutants on a Rotary-Wing Unmanned Aerial Vehicle: Development and Application

by Xiaodie Kong, Xiaoya Dou, Hefan Liu, Guangming Shi, Xingyu Xiang, Qinwen Tan, Danlin Song, Fengxia Huang, Xiaoling Zhou, Hongbin Jiang, Pu Wang, Li Zhou and Fumo Yang

Atmosphere 2025, 16(5), 613; https://doi.org/10.3390/atmos16050613 - 17 May 2025

Viewed by 122

Abstract

Complex air pollution, including particulate matter and ozone, is a significant environmental issue in China, with volatile organic compounds (VOCs) as key precursors. Traditional ground-based monitoring methods struggle to capture the vertical distribution and changes of pollutants in the troposphere. To address this, [...] Read more.

Complex air pollution, including particulate matter and ozone, is a significant environmental issue in China, with volatile organic compounds (VOCs) as key precursors. Traditional ground-based monitoring methods struggle to capture the vertical distribution and changes of pollutants in the troposphere. To address this, we developed a vertical monitoring and sampling platform using a quadcopter unmanned aerial vehicle (UAV). The platform, equipped with lightweight quartz sampling canisters and miniaturized sensors, collects air samples for VOC analysis and vertical data on meteorological parameters and particulate matter. Performance tests showed the quartz canisters had less than 15% adsorption loss, with sample storage stability exceeding 80% over three days. Sensor data showed strong correlations with standard instruments (R² > 0.80). Computational fluid dynamics simulations optimized the sampler’s inlet position and ascertained that ascending flight mitigates rotor-induced air recirculation. Field campaigns were conducted at six sites along the Chengdu Metropolitan Circle Ring Expressway. Vertical data from 0~300 m revealed particulate matter concentrations peaked at 50~70 m. Near-surface VOCs were dominated by alkanes, while aromatics were found concentrated at 150~250 m, indicating significant regional transport influences. The results confirmed the platform’s effectiveness for pollutant distribution analysis. Full article

(This article belongs to the Special Issue Emissions of Volatile Organic Compounds (VOCs): Characterization, Environmental Impacts and Control)

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17 pages, 4685 KiB

Open AccessArticle

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

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

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

Viewed by 86

Abstract

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

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

(This article belongs to the Section Meteorology)

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22 pages, 6558 KiB

Open AccessArticle

Characteristics of Meteorological Droughts Across Different Climatic Zones in Benin

by Abdoul-Aziz Bio Sidi D. Bouko, Bing Gao, Jabir Abubakar, Richard F. Annan, Randal D. Djessou, Admire M. Mutelo, Zozo El-Saadani and Lekoueiry Dehah

Atmosphere 2025, 16(5), 611; https://doi.org/10.3390/atmos16050611 - 17 May 2025

Viewed by 112

Abstract

This study investigates meteorological drought characteristics across three climatic zones in Benin using the SPEI (Standardized Precipitation Evapotranspiration Index) and SPI (Standardized Precipitation Index). A comprehensive statistical approach was employed, including the Mann–Kendall trend test, drought duration and intensity analysis, Pearson correlation, cross-wavelet [...] Read more.

This study investigates meteorological drought characteristics across three climatic zones in Benin using the SPEI (Standardized Precipitation Evapotranspiration Index) and SPI (Standardized Precipitation Index). A comprehensive statistical approach was employed, including the Mann–Kendall trend test, drought duration and intensity analysis, Pearson correlation, cross-wavelet transform, and the Standardized Relative Air Humidity Index (SRHI), to assess drought patterns and trends. The findings indicate increasing consistency between SPI and SPEI trends at longer timescales, though significant regional variations persist. In Zone 1 (northern Benin), SPI exhibited an increasing trend across all timescales, whereas SPEI demonstrated a decreasing trend at shorter timescales. In contrast, in Zones 2 (central Benin) and 3 (south Benin), both indices generally displayed a decreasing trend, except at the one-month scale. An analysis of drought duration and intensity revealed that, at shorter timescales (SPI and SPEI at 1- and 3-month intervals), the longest droughts occurred in Zones 1 and 3, while the most intense events were recorded in Zone 2. At longer timescales (SPI and SPEI at 6- and 12-month intervals), Zone 2 experienced the longest droughts, whereas Zone 3 exhibited the highest intensities. These findings illustrate the need for monitoring strategies tailored to a given area’s characteristics. Despite these insights, data uncertainties and regional differences present challenges for drought investigation. Future studies should incorporate more datasets and investigate different drought indices to improve decision-making and improve strategies for safeguarding Benin’s agricultural sector, ecosystems, and food supply. Full article

(This article belongs to the Section Climatology)

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17 pages, 3896 KiB

Open AccessArticle

Disparities in Fine Particulate Matter Air Pollution Exposures at the US–Mexico Border: The Intersection of Race/Ethnicity and Older Age

by Timothy W. Collins, Colby M. Child, Sara E. Grineski and Mathilda Scott

Atmosphere 2025, 16(5), 610; https://doi.org/10.3390/atmos16050610 - 17 May 2025

Viewed by 132

Abstract

Environmental justice research in the United States (US) documents greater air pollution exposures for Hispanic/Latino vs. non-Hispanic White groups. EJ research has not focused on the intersection of race/ethnicity and older age nor short-term fine particulate matter (PM_2.5) exposures. We address [...] Read more.

Environmental justice research in the United States (US) documents greater air pollution exposures for Hispanic/Latino vs. non-Hispanic White groups. EJ research has not focused on the intersection of race/ethnicity and older age nor short-term fine particulate matter (PM_2.5) exposures. We address these knowledge gaps by studying US metropolitan area census tracts within 100 km of the US–Mexico border, a region with serious air quality issues. We use US Census American Community Survey data to construct sociodemographic variables and Environmental Protection Agency Downscaler data to construct long-term and short-term measures of PM_2.5 exposure. Using multivariable generalized estimating equations, we test for differences in PM_2.5 exposures between census tracts with higher vs. lower proportions of older Hispanic/Latino residents and older non-Hispanic White residents. The results indicate that as the proportion of the Hispanic/Latino population ≥ 65 years of age increases, long-term and short-term PM_2.5 exposures significantly increase. In contrast, as the proportion of the non-Hispanic White population ≥ 65 years of age increases, changes in long-term and short-term PM_2.5 exposures are statistically non-significant. These findings illuminate how race/ethnicity and older age intersect in shaping PM_2.5 exposure disparities and may inform efforts to mitigate air pollution exposures for overburdened people along the US–Mexico border. Full article

(This article belongs to the Section Air Quality)

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14 pages, 1502 KiB

Open AccessArticle

Relationships Among Atmospheric Suspended Particulates with Different Sizes: A Case Study of Chongqing City

by Yan Gui and Haiyang Wang

Atmosphere 2025, 16(5), 609; https://doi.org/10.3390/atmos16050609 - 17 May 2025

Viewed by 147

Abstract

The current study predicts that there would be scaling relationships among atmospheric suspended particulate materials (PMs) with different diameters. Through sampling the particulate materials concentration over different types of land use in municipal areas in Chongqing, analyzing the respective data of the independent [...] Read more.

The current study predicts that there would be scaling relationships among atmospheric suspended particulate materials (PMs) with different diameters. Through sampling the particulate materials concentration over different types of land use in municipal areas in Chongqing, analyzing the respective data of the independent concentrations of particulate materials varying in sizes, and testing the predictions, it is found that: (1) there are generally a negative relationships between falling dust of large particulate size (diameter > 10 μm) and floating dust of small ones (diameter ≤ 10 μm); (2) there are positive correlations among the fine particulate materials varying in sizes of iPM10, iPM2.5, and iPM1; (3) there is a disproportionately increase between the particulate materials varying in sizes compared to the respective control; (4) there is a declining-and-rising tendency between the particulate materials reduction rate and the increase in particulate materials along a particulate-size-decline gradient. The results of this study may contribute to understanding the law of the interactions of particulate materials with different particle sizes in the atmosphere and lay a theoretical foundation for the elimination of the atmospheric suspended pollutants. Full article

(This article belongs to the Special Issue Recent Advances in Urban Climate)

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18 pages, 5282 KiB

Open AccessArticle

Climate Adaptability Analysis of Traditional Dwellings in Mountain Terraced Areas: A Case Study of ‘Mushroom Houses’ in the Hani Terraces of Yunnan, China

by Luyao Hu, Yinong Liu, Xinkai Li and Pengbo Yan

Atmosphere 2025, 16(5), 608; https://doi.org/10.3390/atmos16050608 - 16 May 2025

Viewed by 65

Abstract

This study examines the climate adaptability of traditional Hani ‘Mushroom Houses’ located in the rice terrace region of Honghe Hani Autonomous Prefecture, Yunnan, China. By analyzing 30 years of meteorological data, the study identifies the local climatic characteristics of high temperatures, high humidity, [...] Read more.

This study examines the climate adaptability of traditional Hani ‘Mushroom Houses’ located in the rice terrace region of Honghe Hani Autonomous Prefecture, Yunnan, China. By analyzing 30 years of meteorological data, the study identifies the local climatic characteristics of high temperatures, high humidity, and significant diurnal temperature variations. The thermal comfort voting method was used to establish a quantitative relationship between the Physiological Equivalent Temperature (PET) index and residents’ subjective thermal perceptions, thereby assessing seasonal variations in thermal comfort. Field measurements of indoor and outdoor temperature, humidity, and wind speed were conducted in May and December 2023 to evaluate thermal interactions between rooms. This study demonstrated: (1) the critical roles of building orientation (e.g., northwest-facing design), functional layout (e.g., multi-story zoning), and structural forms (e.g., thick walls, thatched roofs) in regulating temperature and humidity. (2) Confirmed that Hani ‘Mushroom Houses’ stabilize indoor environments through passive strategies, including material selection (wood, rammed earth), natural ventilation (cross-draft design), and spatial organization (climate-buffering storage layers). (3) Provided empirical evidence for optimizing traditional dwellings (e.g., enhanced insulation, ventilation improvements) and advancing sustainable practices in similar climatic regions. Full article

(This article belongs to the Section Biometeorology and Bioclimatology)

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19 pages, 6942 KiB

Open AccessArticle

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

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

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

Viewed by 117

Abstract

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

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

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

, and the annual average NEP was 60.31

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

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

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

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26 pages, 6795 KiB

Open AccessArticle

Analysis of Time-Domain Characteristics of Microsecond-Scale Repetitive Pulse Discharge Events in Lightning

by Jinxing Shen, Zheng Sun, Lihua Shi and Shi Qiu

Atmosphere 2025, 16(5), 606; https://doi.org/10.3390/atmos16050606 - 16 May 2025

Viewed by 39

Abstract

To clarify the background of multiple burst (MB) specifications in the aviation lightning test standards, a broadband lightning electromagnetic field measurement system was employed to collect 91 sets of VLF/LF band nature flash data. A total of 719 typical repetitive pulse (RP) groups [...] Read more.

To clarify the background of multiple burst (MB) specifications in the aviation lightning test standards, a broadband lightning electromagnetic field measurement system was employed to collect 91 sets of VLF/LF band nature flash data. A total of 719 typical repetitive pulse (RP) groups were identified, and 163,589 single pulse samples were analyzed statistically. The variational mode decomposition (VMD) method and a trend-free correlation on index (TFCI) were used to extract RPs from the slowly varying trends and high-frequency noises from the measured data. The time-domain characteristics of four kinds of RPs corresponding to the lightning discharge events—initial breakdown pulse (IBP), regular pulse bursts (RPB), chaotic pulse train (CPT), and dart-stepped leader (DSL)—were investigated. By comparing previous statistics and the definition in current international aviation standards, the intrinsic correlation between RPs and the defined parameters of MBs was explored. New recommendations for the MB test standard were subsequently proposed. Full article

(This article belongs to the Section Upper Atmosphere)

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10 pages, 643 KiB

Open AccessArticle

The Risk of Developing Aphasia and Exposure to Air Pollution in Taiwan

by Jinyi Hung, Pei-Chun Lin, Chiu-Ying Chen, Stella Chin-Shaw Tsai, Ruey-Hwang Chou, Cheng-Li Lin, Der-Yang Cho, Ching-Liang Hsieh, Chang-Yin Lee, Kuang-Hsi Chang, Yi-Chao Hsu and Tai-Lin Huang

Atmosphere 2025, 16(5), 605; https://doi.org/10.3390/atmos16050605 - 16 May 2025

Viewed by 124

Abstract

(1) Background: The relationship between air pollution and the risk of developing aphasia is still unclear. We aimed to evaluate air pollution exposure as a risk factor for developing aphasia in Taiwan. (2) Methods: This retrospective population-based cohort study used the Longitudinal Generation [...] Read more.

(1) Background: The relationship between air pollution and the risk of developing aphasia is still unclear. We aimed to evaluate air pollution exposure as a risk factor for developing aphasia in Taiwan. (2) Methods: This retrospective population-based cohort study used the Longitudinal Generation Tracking Database (LGTD) and the Taiwan Air Quality Monitoring Database (TAQMD). The incidence rate ratio (IRR) and adjusted hazard ratio (aHR) were calculated to examine the association between aphasia and exposure to six air pollutants: sulfur oxide (SO₂), carbon monoxide (CO), nitric oxide (NO), nitrogen oxide (NOx), and particulate matter (PM_2.5, PM₁₀) from 2003 to 2017. (3) Results: The incidence rate ratio (IRR) of aphasia showed that individuals with high levels of SO₂, CO, and NO were at a higher risk of developing aphasia. Increased exposure to airborne particulate matter (PM_2.5 and PM₁₀) also increased the risk of developing aphasia. The adjusted HRs of the aphasia risk were statistically significant for all the air pollutants at higher concentrations. (4) Conclusions: Individuals exposed to ambient air pollutants have a significantly higher risk of developing aphasia. The greater the exposure to airborne particulate matter and gaseous pollutants, the more likely individuals are to develop aphasia. Full article

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

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32 pages, 10365 KiB

Open AccessArticle

Development and Evaluation of the Online Hybrid Model CAMx-LPiG

by Andrea Piccoli, Valentina Agresti, Giovanni Lonati and Guido Pirovano

Atmosphere 2025, 16(5), 604; https://doi.org/10.3390/atmos16050604 - 16 May 2025

Viewed by 99

Abstract

CAMx-LPiG (Comprehensive Air Quality Model with Extensions—Linear Plume in Grid) is an online hybrid model based on the Chemistry and Transport Model (CTM) CAMx, which includes a sub-grid scale module to simulate the dispersion of linear road traffic emissions called LPiG. LPiG is [...] Read more.

CAMx-LPiG (Comprehensive Air Quality Model with Extensions—Linear Plume in Grid) is an online hybrid model based on the Chemistry and Transport Model (CTM) CAMx, which includes a sub-grid scale module to simulate the dispersion of linear road traffic emissions called LPiG. LPiG is a plume in grid module specifically developed by extending the capabilities of the Lagrangian puff sub-grid model available in CAMx. The online integration of the local scale model within the Eulerian CTM allows for a multiscale simulation of air quality from the regional scale to the urban scale, preserving a coherent description of the chemical state of the atmosphere at all spatial scales and avoiding any double counting of the emissions simulated by the sub-grid module. In this work, the model is presented and evaluated against measured NO₂ concentrations for the city of Milan for the month of January 2017. The model can introduce road traffic-induced gradient in NO₂ concentration at sub-grid resolution. Moreover, CAMx-LPiG has been shown to reduce bias compared to CAMx stand-alone simulations. Full article

(This article belongs to the Special Issue Urban Air Pollution, Meteorological Conditions and Human Health)

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19 pages, 5467 KiB

Open AccessArticle

Seasonal and Diurnal Variations of Indoor PM_2.5 in Six Households in Akure, Nigeria

by Sawanya Saetae, Francis Olawale Abulude, Kazushi Arasaki, Mohammed Mohammed Ndamitso, Akinyinka Akinnusotu, Samuel Dare Oluwagbayide, Yutaka Matsumi, Kazuaki Kawamoto and Tomoki Nakayama

Atmosphere 2025, 16(5), 603; https://doi.org/10.3390/atmos16050603 - 16 May 2025

Viewed by 51

Abstract

Seasonal, diurnal, and site-to-site variations in indoor PM_2.5 concentrations in Akure, a city in southwestern Nigeria, are investigated by continuous observations using low-cost sensors in six households. Significant seasonal variations were observed, with the highest monthly PM_2.5 concentrations occurring in the [...] Read more.

Seasonal, diurnal, and site-to-site variations in indoor PM_2.5 concentrations in Akure, a city in southwestern Nigeria, are investigated by continuous observations using low-cost sensors in six households. Significant seasonal variations were observed, with the highest monthly PM_2.5 concentrations occurring in the dry season, both indoors and outdoors. Significant seasonal variations with higher PM_2.5 levels during the dry season were observed, with mean PM_2.5 concentrations of 55 μg/m³ in the kitchen and 48 μg/m³ in the living rooms, compared to those during the wet season (23 μg/m³ in the kitchen and 14 μg/m³ in the living rooms). The kitchen-to-outdoor and indoor-to-outdoor PM_2.5 ratios increased particularly during the morning and evening hours at several sites, suggesting significant contributions from cooking activities in the kitchen, as well as the transfer of PM_2.5 into the living room. An assessment of PM_2.5 exposure risks among 32 residents in the studied households revealed higher risks among individuals who cook routinely. This study underscores the importance of addressing indoor air pollution alongside outdoor pollution, particularly by improving ventilation and reducing cooking emissions, to effectively minimize exposure risks. Full article

(This article belongs to the Section Air Quality)

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23 pages, 8237 KiB

Open AccessArticle

Evaluation of Time Delay and Cumulative Effects of Meteorological Drought on Net Primary Productivity of Vegetation in the Upper Reaches of the Yellow River, China

by Huazhu Xue, Zhi Li, Guotao Dong and Hao Wang

Atmosphere 2025, 16(5), 602; https://doi.org/10.3390/atmos16050602 - 16 May 2025

Viewed by 34

Abstract

As a critical region for ecological construction in China, the upper Yellow River is still relatively short of research on the time-lag and cumulative effects of regional-scale drought on vegetation growth. Therefore, based on net primary productivity (NPP) estimated by the improved CASA [...] Read more.

As a critical region for ecological construction in China, the upper Yellow River is still relatively short of research on the time-lag and cumulative effects of regional-scale drought on vegetation growth. Therefore, based on net primary productivity (NPP) estimated by the improved CASA (Carnegie–Ames–Stanford approach) model and multi-time scale SPEI, trend analysis, significance test and partial correlation analysis were employed to explore the spatial and temporal patterns of NPP and quantitatively evaluate its response to drought. The results showed that (1) From 2001 to 2022, NPP was higher in the south and lower in the north, decreasing from southwest to northeast, and annual NPP was increasing in 87.9% of the regions. NPP in spring, summer and autumn has been significantly improved. (2) In terms of interannual and spatial distribution, except for spring and winter, annual, summer and autumn all showed an insignificant trend of humidification. (3) The lag and cumulative effects of drought on vegetation in most areas are positively correlated. About 82.58% of NPP in the growing season has a time-lag effect with drought, which mainly focuses on 1–2 months. The average lag time was 3.6 months, indicating that NPP had the strongest correlation with the meteorological drought index of the previous 3.6 months. For cumulative effect, about 66.14% of NPP had a cumulative effect on drought, and the cumulative time scales were mainly March, April, November and December. With the worsening of drought conditions, the effect of drought on NPP is enhanced. These findings enhance the understanding of the long-term consequences of drought on terrestrial ecosystems and provide a basis for the development of mitigation and adaptation strategies aimed at alleviating the adverse effects of drought on agriculture and ecosystems. Full article

(This article belongs to the Special Issue Drought Monitoring, Prediction and Impacts (2nd Edition))

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17 pages, 12037 KiB

Open AccessArticle

The Long-Delayed Response of a Cyclonic Ocean Eddy to the Passage of Typhoons Hinnamnor and Muifa

by Jiaqi Wang and Yineng Rong

Atmosphere 2025, 16(5), 601; https://doi.org/10.3390/atmos16050601 - 16 May 2025

Viewed by 71

Abstract

A cyclonic ocean eddy (COE) exhibited an extraordinarily prolonged response to sequential typhoons Hinnamnor (1 September 2022) and Muifa (11 September 2022), reaching its peak strength 20 days post-typhoon (1 October 2022), almost double the typical 7–14-day latency for mesoscale eddies. In this [...] Read more.

A cyclonic ocean eddy (COE) exhibited an extraordinarily prolonged response to sequential typhoons Hinnamnor (1 September 2022) and Muifa (11 September 2022), reaching its peak strength 20 days post-typhoon (1 October 2022), almost double the typical 7–14-day latency for mesoscale eddies. In this study, we use a functional analysis apparatus, namely the multiscale window transform (MWT) and the MWT-based theory of canonical transfer and multiscale energetics analysis, to investigate the dynamics underlying this phenomenon. The original fields, which are obtained from HYCOM reanalysis data, are initially decomposed into three parts in three different scale windows, respectively, with the eddy-scale window (or COE window) lying in between. By examining the evolution of eddy kinetic energy (EKE), the response can be divided into two stages. From the energetic diagnosis, the COE’s response is not only visible at the surface but was even strengthened through interactions between the subsurface and surface, with vertical transport playing a crucial role. This response can be categorized into two stages: The energetics of the long-delayed response is in the first stage due to the storage of the eddy-scale available potential energy (EAPE) from the high-frequency scale window, where the typhoon injects energy through an inverse canonical transfer. The resulting EAPE is transported downward to the sub-surface. In the second stage, the subsurface EKE is carried upward to the surface via pressure work, leading to an explosive growth of the COE. These findings illuminate the significance of subsurface–surface interactions in modulating long-delayed eddy responses. 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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23 pages, 1667 KiB

Open AccessArticle

Experience from Research on Indoor and Outdoor Air Quality in the Poznań Agglomeration

by Małgorzata Basińska and Michał Michałkiewicz

Atmosphere 2025, 16(5), 600; https://doi.org/10.3390/atmos16050600 - 16 May 2025

Viewed by 32

Abstract

This article explores how the location of a building in an urban area, the level of external air pollution, and the way a residence is used can affect indoor air quality. To assess this, this study used measurements of physical and chemical pollutants, [...] Read more.

This article explores how the location of a building in an urban area, the level of external air pollution, and the way a residence is used can affect indoor air quality. To assess this, this study used measurements of physical and chemical pollutants, as well as microbiological measurements, including counts of various bacteria and microscopic fungi. These included counts of mesophilic and psychrophilic bacteria, mannitol-positive and mannitol-negative Staphylococcus, Actinobacteria, Pseudomonas fluorescens, and microscopic fungi. The research involved analysing indoor and outdoor air quality in 38 selected spaces within buildings in the city of Poznań during the heating season. The study found that the eastern part of the city showed the highest levels of fungal contamination in the external environment. Furthermore, distinct differences were observed between the presence of microorganisms indoors and outdoors based on the results of bacterial and fungal aerosol studies. The authors advocate for including microbiological studies as part of standard air quality assessment indicators to reveal the extent and source of contamination, as similar issues may be present in cities around the world. Full article

(This article belongs to the Special Issue Air Quality in Poland (2nd Edition))

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