Journal Description
Atmosphere
Atmosphere
is an international, peer-reviewed, open access journal of scientific studies related to the atmosphere published monthly online by MDPI. The Italian Aerosol Society (IAS) and Working Group of Air Quality in European Citizen Science Association (ECSA) are affiliated with Atmosphere and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, GEOBASE, GeoRef, Inspec, CAPlus / SciFinder, Astrophysics Data System, and other databases.
- Journal Rank: CiteScore - Q2 (Environmental Science (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.7 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our editors and authors say about the Atmosphere.
- Companion journal: Meteorology.
Impact Factor:
2.9 (2022);
5-Year Impact Factor:
3.0 (2022)
Latest Articles
Assessment of Indoor Radon Gas Concentration in Latvian Households
Atmosphere 2024, 15(5), 611; https://doi.org/10.3390/atmos15050611 (registering DOI) - 18 May 2024
Abstract
Exposure to radon gas in households presents serious health risks, including an increased likelihood of lung cancer. Following the COVID-19 pandemic, the change in individual habits has led to more time spent in indoor environments with remote activities; thus, the need to raise
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Exposure to radon gas in households presents serious health risks, including an increased likelihood of lung cancer. Following the COVID-19 pandemic, the change in individual habits has led to more time spent in indoor environments with remote activities; thus, the need to raise the awareness of air quality in dwellings and to mitigate the exposure of inhabitants to radon has emerged. This study investigated radon gas concentrations in the air of Latvian dwellings. RadTrack2 passive detectors were deployed in a representative sample of households across 106 municipalities of Latvia (98% of the territory), yielding data from 487 households (973 detectors). The data revealed a median radon concentration of 52 Bq/m3 (Q1 and Q3 were 29 and 93 Bq/m3), with the majority of samples (95.6%) falling below the national reference limit of 200 Bq/m3. The building type and presence of a cellar significantly impacted radon levels, with structures lacking cellars and older buildings exhibiting higher concentrations. Mechanical ventilation proved to be more effective in reducing radon levels, compared to natural ventilation. These findings emphasize the necessity of proactive measures to mitigate indoor radon exposure and to ensure the well-being of occupants. Additionally, the dissemination of research data on radon exposure through open-access scientific publications is vital for raising awareness and implementing effective mitigation strategies.
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(This article belongs to the Special Issue Indoor Air Quality Control)
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ECMWF Ensemble Forecasts of Six Tropical Cyclones That Formed during a Long-Lasting Rossby Wave Breaking Event in the Western North Pacific
by
Russell L. Elsberry, Hsiao-Chung Tsai, Wei-Chia Chin and Timothy P. Marchok
Atmosphere 2024, 15(5), 610; https://doi.org/10.3390/atmos15050610 - 17 May 2024
Abstract
The ECMWF‘s ensemble (ECEPS) predictions are documented for the lifecycles of six tropical cyclones (TCs) that formed during a long-lasting Rossby wave breaking event in the western North Pacific. All six TC tracks started between 20° N and 25° N, and between 136°
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The ECMWF‘s ensemble (ECEPS) predictions are documented for the lifecycles of six tropical cyclones (TCs) that formed during a long-lasting Rossby wave breaking event in the western North Pacific. All six TC tracks started between 20° N and 25° N, and between 136° E and 160° E. All five typhoons recurved north of 30° N, and the three typhoons that did not make landfall had long tracks to 50° N and beyond. The ECEPS weighted mean vector motion track forecasts from pre-formation onward are quite accurate, with track forecast spreads that are primarily related to initial position uncertainties. The ECEPS intensity forecasts have been validated relative to the Joint Typhoon Warning Center (JTWC) Working Best Track (WBT) intensities (when available). The key results for Tokage (11 W) were the ECEPS forecasts of the intensification to a peak intensity of 100 kt, and then a rapid decay as a cold-core cyclone. For Hinnamnor (12 W), the key result was the ECEPS intensity forecasts during the post-extratropical transition period when Hinnamnor was rapidly translating poleward through the Japan Sea. For Muifa (14 W), the key advantage of the ECEPS was that intensity guidance was provided for longer periods than the JTWC 5-day forecast. The most intriguing aspect of the ECEPS forecasts for post-Merbok (15 W) was its prediction of a transition to an intense, warm-core vortex after Merbok had moved beyond 50° N and was headed toward the Aleutian Islands. The most disappointing result was that the ECEPS over-predicted the slow intensification rate of Nanmadol (16 W) until the time-to-typhoon (T2TY), but then failed to predict the large rapid intensification (RI) following the T2TY. The tentative conclusion is that the ECEPS model‘s physics are not capable of predicting the inner-core spin-up rates when a small inner-core vortex is undergoing large RI.
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(This article belongs to the Special Issue Typhoon/Hurricane Dynamics and Prediction (2nd Edition))
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Investigation of the Historical Trends and Variability of Rainfall Patterns during the March–May Season in Rwanda
by
Constance Uwizewe, Li Jianping, Théogène Habumugisha and Ahmad Abdullahi Bello
Atmosphere 2024, 15(5), 609; https://doi.org/10.3390/atmos15050609 - 17 May 2024
Abstract
This study explores the spatiotemporal variability and determinants of rainfall patterns during the March to May (MAM) season in Rwanda, incorporating an analysis of teleconnections with oceanic–atmospheric indices over the period 1983–2021. Utilizing the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset,
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This study explores the spatiotemporal variability and determinants of rainfall patterns during the March to May (MAM) season in Rwanda, incorporating an analysis of teleconnections with oceanic–atmospheric indices over the period 1983–2021. Utilizing the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset, the study employs a set of statistical tools including standardized anomalies, empirical orthogonal functions (EOF), Pearson correlation, the Mann–Kendall (MK) trend test, and Sen’s slope estimator to dissect the intricacies of rainfall variability, trends, and their association with large-scale climatic drivers. The findings reveal a distinct southwest to northwest rainfall gradient across Rwanda, with the MK test signaling a decline in annual precipitation, particularly in the southwest. The analysis for the MAM season reveals a general downtrend in rainfall, attributed in part to teleconnections with the Indian Ocean Sea surface temperatures (SSTs). Notably, the leading EOF mode for MAM rainfall demonstrates a unimodal pattern, explaining a significant 51.19% of total variance, and underscoring the pivotal role of atmospheric dynamics and moisture conveyance in shaping seasonal rainfall. The spatial correlation analysis suggests a modest linkage between MAM rainfall and the Indian Ocean Dipole, indicating that negative (positive) phases are likely to result in anomalously wet (dry) conditions in Rwanda. This comprehensive assessment highlights the intricate interplay between local rainfall patterns and global climatic phenomena, offering valuable insights into the meteorological underpinnings of rainfall variability during Rwanda’s critical MAM season.
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(This article belongs to the Section Meteorology)
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Resonant Forcing by Solar Declination of Rossby Waves at the Tropopause and Implications in Extreme Events, Precipitation, and Heat Waves—Part 1: Theory
by
Jean-Louis Pinault
Atmosphere 2024, 15(5), 608; https://doi.org/10.3390/atmos15050608 - 17 May 2024
Abstract
The purpose of this first article is to provide a physical basis for atmospheric Rossby waves at the tropopause to clarify their properties and improve our knowledge of their role in the genesis of extreme precipitation and heat waves. By analogy with the
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The purpose of this first article is to provide a physical basis for atmospheric Rossby waves at the tropopause to clarify their properties and improve our knowledge of their role in the genesis of extreme precipitation and heat waves. By analogy with the oceanic Rossby waves, the role played by the pycnocline in ocean Rossby waves is replaced here by the interface between the polar jet and the ascending air column at the meeting of the polar and Ferrel cell circulation or between the subtropical jet and the descending air column at the meeting of the Ferrel and Hadley cell circulation. In both cases, the Rossby waves are suitable for being resonantly forced in harmonic modes by tuning their natural period to the forcing period. Here, the forcing period is one year as a result of the variation in insolation due to solar declination. A search for cause-and-effect relationships is performed from the joint representation of the amplitude and phase of (1) the velocity of the cold or warm modulated airflows at 250 mb resulting from Rossby waves, (2) the geopotential height at 500 mb, and (3) the precipitation rate or ground air temperature. This is for the dominant harmonic mode whose period can be 1/16, 1/32, or 1/64 year, which reflects the intra-seasonal variations in the rising and falling air columns at the meeting of the polar, Ferrel, and Hadley cell circulation. Harmonics determine the duration of blocking. Two case studies referring to extreme cold and heat waves are presented. Dual cyclone–anticyclone systems seem to favor extreme events. They are formed by two joint vortices of opposite signs reversing over a period, concomitantly with the involved modulated airflows at the tropopause. A second article will be oriented toward (1) the examination of different case studies in order to ascertain the common characteristics of Rossby wave patterns leading to extreme events and (2) a map of the globe revealing future trends in the occurrence of extreme events.
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(This article belongs to the Special Issue Prediction and Modeling of Extreme Weather Events)
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Elucidating the Effects of COVID-19 Lockdowns in the UK on the O3-NOx-VOC Relationship
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Rayne Holland, Katya Seifert, Eric Saboya, M. Anwar H. Khan, Richard G. Derwent and Dudley E. Shallcross
Atmosphere 2024, 15(5), 607; https://doi.org/10.3390/atmos15050607 - 16 May 2024
Abstract
The unprecedented reductions in anthropogenic emissions over the COVID-19 lockdowns were utilised to investigate the response of ozone (O3) concentrations to changes in its precursors across various UK sites. Ozone, volatile organic compounds (VOCs) and NOx (NO+NO2) data
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The unprecedented reductions in anthropogenic emissions over the COVID-19 lockdowns were utilised to investigate the response of ozone (O3) concentrations to changes in its precursors across various UK sites. Ozone, volatile organic compounds (VOCs) and NOx (NO+NO2) data were obtained for a 3-year period encompassing the pandemic period (January 2019–December 2021), as well as a pre-pandemic year (2017), to better understand the contribution of precursor emissions to O3 fluctuations. Compared with pre-lockdown levels, NO and NO2 declined by up to 63% and 42%, respectively, over the lockdown periods, with the most significant changes in pollutant concentrations recorded across the urban traffic sites. O3 levels correspondingly increased by up to 30%, consistent with decreases in the [NO]/[NO2] ratio for O3 concentration response. Analysis of the response of O3 concentrations to the NOx reductions suggested that urban traffic, suburban background and suburban industrial sites operate under VOC-limited regimes, while urban background, urban industrial and rural background sites are NOx-limited. This was in agreement with the [VOC]/[NOx] ratios determined for the London Marylebone Road (LMR; urban traffic) site and the Chilbolton Observatory (CO; rural background) site, which produced values below and above 8, respectively. Conversely, [VOC]/[NOx] ratios for the London Eltham (LE; suburban background) site indicated NOx-sensitivity, which may suggest the [VOC]/[NOx] ratio for O3 concentration response may have had a slight NOx-sensitive bias. Furthermore, O3 concentration response with [NO]/[NO2] and [VOC]/[NOx] were also investigated to determine their relevance and accuracy in identifying O3-NOx-VOC relationships across UK sites. While the results obtained via utilisation of these metrics would suggest a shift in photochemical regime, it is likely that variation in O3 during this period was primarily driven by shifts in oxidant (OX; NO2 + O3) equilibrium as a result of decreasing NO2, with increased O3 transported from Europe likely having some influence.
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(This article belongs to the Special Issue Mechanisms of Urban Ozone Pollution)
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Impacts of Climate Change and Adaptation Strategies for Rainfed Barley Production in the Almería Province, Spain
by
Francesco Saretto, Bishwajit Roy, Ricardo Encarnação Coelho, Alfredo Reder, Giusy Fedele, Robert Oakes, Luigia Brandimarte and Tiago Capela Lourenço
Atmosphere 2024, 15(5), 606; https://doi.org/10.3390/atmos15050606 - 16 May 2024
Abstract
Mediterranean water-stressed areas face significant challenges from higher temperatures and increasingly severe droughts. We assess the effect of climate change on rainfed barley production in the aridity-prone province of Almería, Spain, using the FAO AquaCrop model. We focus on rainfed barley growth by
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Mediterranean water-stressed areas face significant challenges from higher temperatures and increasingly severe droughts. We assess the effect of climate change on rainfed barley production in the aridity-prone province of Almería, Spain, using the FAO AquaCrop model. We focus on rainfed barley growth by the mid-century (2041–2070) and end-century (2071–2100) time periods, using three Shared Socio-economic Pathway (SSP)-based scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. Using the paired t-test, Spearman and Pearson correlation coefficient, Root Mean Squared Error, and relative Root Mean Squared Error, we verified AquaCrop’s ability to capture local multi-year trends (9 or more years) using standard barley crop parameters, without local recalibration. Starting with a reference Initial Soil Water Content (ISWC), different soil water contents within barley rooting depth were modelled to account for decreases in soil water availability. We then evaluated the efficiency of different climate adaptation strategies: irrigation, mulching, and changing sowing dates. We show average yield changes of +14% to −44.8% (mid-century) and +12% to −55.1% (end-century), with ISWC being the main factor determining yields. Irrigation increases yields by 21.1%, utilizing just 3% of Almería’s superficial water resources. Mulches improve irrigated yield performances by 6.9% while reducing irrigation needs by 40%. Changing sowing dates does not consistently improve yields. We demonstrate that regardless of the scenario used, climate adaptation of field barley production in Almería should prioritize limiting soil water loss by combining irrigation with mulching. This would enable farmers in Almería’s northern communities to maintain their livelihoods, reducing the province’s reliance on horticulture while continuing to contribute to food security goals.
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(This article belongs to the Special Issue Agrometeorology, Agricultural Water Management and Impacts of Extreme Events (2nd Edition))
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Hierarchical Predictions of Fine-to-Coarse Time Span and Atmospheric Field Reconstruction for Typhoon Track Prediction
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Shengye Yan, Zhendong Zhang and Wei Zheng
Atmosphere 2024, 15(5), 605; https://doi.org/10.3390/atmos15050605 - 16 May 2024
Abstract
The prediction of typhoon tracks in the Northwest Pacific is key to reducing human casualties and property damage. Traditional numerical forecasting models often require substantial computational resources, are high-cost, and have significant limitations in prediction speed. This research is dedicated to using deep
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The prediction of typhoon tracks in the Northwest Pacific is key to reducing human casualties and property damage. Traditional numerical forecasting models often require substantial computational resources, are high-cost, and have significant limitations in prediction speed. This research is dedicated to using deep learning methods to address the shortcomings of traditional methods. Our method (AFR-SimVP) is based on a large-kernel convolutional spatio-temporal prediction network combined with multi-feature fusion for forecasting typhoon tracks in the Northwest Pacific. In order to more effectively suppress the effect of noise in the dataset to enhance the generalization ability of the model, we use a multi-branch structure, incorporate an atmospheric reconstruction subtask, and propose a second-order smoothing loss to further improve the prediction ability of the model. More importantly, we innovatively propose a multi-time-step typhoon prediction network (HTAFR-SimVP) that does not use the traditional recurrent neural network family of models at all. Instead, through fine-to-coarse hierarchical temporal feature extraction and dynamic self-distillation, multi-time-step prediction is achieved using only a single regression network. In addition, combined with atmospheric field reconstruction, the network achieves integrated prediction for multiple tasks, which greatly enhances the model’s range of applications. Experiments show that our proposed network achieves optimal performance in the 24 h typhoon track prediction task. Our regression network outperforms previous recurrent network-based typhoon prediction models in the multi-time-step prediction task and also performs well in multiple integration tasks.
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(This article belongs to the Special Issue Deep Learning Algorithms for Weather Forecasting and Climate Prediction)
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Experimental Study on Evaporation and Micro-Explosion Characteristics of Ethanol and Diesel Blended Droplets
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Yixuan Zhang, Kesheng Meng, Lin Bao, Qizhao Lin and Svitlana Pavlova
Atmosphere 2024, 15(5), 604; https://doi.org/10.3390/atmos15050604 - 15 May 2024
Abstract
In this study, the constant temperature control system of a heating plate was established, ethanol–diesel fuel with different proportions was prepared, and a series of experiments were carried out. The experimental system was used to observe, summarize, and analyze four evaporation and crushing
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In this study, the constant temperature control system of a heating plate was established, ethanol–diesel fuel with different proportions was prepared, and a series of experiments were carried out. The experimental system was used to observe, summarize, and analyze four evaporation and crushing modes of mixed droplets, which were explosion, liquid filament stretching, exocytosis, and ejection mode. The evaporation process of four kinds of mixed droplets in their life cycle was analyzed by normalizing the diameter square. It was proposed that the evaporation process of droplets could be divided into the following three stages: a heating stage, a fluctuating evaporation stage, and an equilibrium evaporation stage. It was also pointed out that the expansion, ejection, and micro-explosion of droplets were the causes of fluctuating evaporation. The concept of expansion and crushing intensity was put forward and the expansion and crushing intensity of ethanol/diesel mixed droplets with different proportions were calculated. The reasons why expansion and crushing intensity first increased and decreased with the increase in ethanol blending ratio were analyzed. Finally, the time proportion of ethanol–diesel mixed droplets in each evaporation stage was calculated, which explained that the time proportion of the instantaneous heating stage showed a parabolic law with the increase in ethanol content.
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(This article belongs to the Special Issue Engine Emissions: Assessment and Control)
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Phenomenology of the Composition of PM2.5 at an Urban Site in Northern France
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Yamina Allouche, Marc Fadel, Amélie Ferté, Anthony Verdin, Frédéric Ledoux and Dominique Courcot
Atmosphere 2024, 15(5), 603; https://doi.org/10.3390/atmos15050603 - 15 May 2024
Abstract
In this work, PM2.5 was sampled at Dunkerque, a medium-sized city located in northern France. The mean concentration of PM2.5 during the sampling period was 12.6 ± 9.5 μg·m−3. Samples were analyzed for elemental and organic carbon (EC/OC), water-soluble
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In this work, PM2.5 was sampled at Dunkerque, a medium-sized city located in northern France. The mean concentration of PM2.5 during the sampling period was 12.6 ± 9.5 μg·m−3. Samples were analyzed for elemental and organic carbon (EC/OC), water-soluble organic carbon (WSOC), humic-like substances (HULIS-C), water-soluble inorganic ions, and major and trace elements. The origin and the variations of species concentrations were examined using elemental enrichment factors, bivariate polar plot representations, and diagnostic concentration ratios. Secondary inorganic ions were the most abundant species (36% of PM2.5), followed by OC (12.5% of PM2.5). Secondary organic carbon (SOC) concentrations were estimated to account for 52% of OC. A good correlation between SOC and WSOC indicated that secondary formation processes significantly contribute to the WSOC concentrations. HULIS-C also represents almost 50% of WSOC. The determination of diagnostic ratios revealed the influence of anthropogenic emission sources such as integrated steelworks and fuel oil combustion. The clustering of 72 h air masses backward trajectories data evidenced that higher concentrations of PM2.5, OC, and secondary inorganic aerosols were recorded when air masses came from north-eastern Europe and the French continental sector, showing the considerable impact of long-range transport on the air quality in northern France.
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(This article belongs to the Special Issue Characteristics and Source Apportionment of Urban Air Pollution)
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Numerical Simulation of the Plant Shelterbelt Configuration Based on Porous Media Model
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Yuhao Zhao, Ning Huang, Jialiang Sun, Kejie Zhan, Xuanmin Li, Bin Han and Jie Zhang
Atmosphere 2024, 15(5), 602; https://doi.org/10.3390/atmos15050602 - 14 May 2024
Abstract
Low-coverage line-belt-pattern protective forests offer significant advantages in terms of wind and sand control measures. It is important to study the windbreak effectiveness of sand-fixing forests with different spacing for the construction and optimization of plant shelterbelt configurations. The effect of plant spacing
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Low-coverage line-belt-pattern protective forests offer significant advantages in terms of wind and sand control measures. It is important to study the windbreak effectiveness of sand-fixing forests with different spacing for the construction and optimization of plant shelterbelt configurations. The effect of plant spacing on the flow field around a row of trees was investigated using the k-ε turbulence model coupled with the porous media model. In order to accurately simplify the complex and stochastic plant constitutive features, we simplify the plant canopy to a circular platform geometry, which introduces a porous media model, and the plant trunk is simulated as a solid cylinder. The simulation results show that windbreaks only affect wind profiles up to 1.25-times the height of the tree; on the leeward side of the canopy, large-spaced shelterbelts provide greater protection in the near-wake zone, while small-spaced shelterbelts are more effective at reducing velocity in the re-equilibration zone. The flow field recovery properties of the trunk and canopy indicate that the canopy wake zone is longer. In this study, we also quantitatively analyze the relationship between average wind protection effectiveness as a function of plant spacing and streamwise distance from the leeward side of the canopy, and the given parameterized scheme shows a power exponential relationship between wind protection effectiveness and plant spacing and a logarithmic relationship with streamwise distance. This scheme can provide a predictive assessment of the effects during the implementation of the plant shelterbelt.
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(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
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Open AccessArticle
Future Projections of Precipitation Extremes for Greece Based on an Ensemble of High-Resolution Regional Climate Model Simulations
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Prodromos Zanis, Aristeidis K. Georgoulias, Kondylia Velikou, Dimitris Akritidis, Alkiviadis Kalisoras and Dimitris Melas
Atmosphere 2024, 15(5), 601; https://doi.org/10.3390/atmos15050601 - 14 May 2024
Abstract
An assessment of the projected changes in precipitation extremes for the 21st century is presented here for Greece and its individual administrative regions. The analysis relies on an ensemble of high-resolution Regional Climate Model (RCM) simulations following various Representative Concentration Pathways (RCP2.6, RCP4.5,
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An assessment of the projected changes in precipitation extremes for the 21st century is presented here for Greece and its individual administrative regions. The analysis relies on an ensemble of high-resolution Regional Climate Model (RCM) simulations following various Representative Concentration Pathways (RCP2.6, RCP4.5, and RCP8.5). The simulated changes in future annual total precipitation (PRTOT) under the examined scenarios are generally negative but statistically non-robust, except towards the end of the century (2071–2100) over high-altitude mountainous regions in Western Greece, Peloponnese, and Crete under RCP8.5. The pattern of change in the number of very heavy precipitation days (R20) is linked to the respective pattern of the PRTOT change with a statistically robust decrease of up to −5 days per year only over parts of the high-altitude mountainous regions in Western Greece, Peloponnese, and Crete for 2071–2100 under RCP8.5. Contrasting the future tendency for decrease in total precipitation and R20, the changes in the intensity of precipitation extremes show a tendency for intensification. However, these change patterns are non-robust for all periods and scenarios. Statistical significance is indicated for the highest 1-day precipitation amount in a year (Rx1day) for the administrative regions of Thessaly, Central Greece, Ionian Islands, and North Aegean under RCP8.5 in 2071–2100. The changes in the contribution of the wettest day per year to the annual total precipitation (RxTratio) are mainly positive but non-robust for most of Greece and all scenarios in the period 2021–2050, becoming more positive and robust in 2071–2100 for RCP8.5. This work highlights the necessity of taking into consideration high-resolution multi-model RCM estimates in future precipitation extremes with various scenarios, for assessing their potential impact on flood episodes and the strategic planning of structure resilience at national and regional level under the anticipated human-induced future climate change.
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(This article belongs to the Special Issue The Drivers and Impacts of Climate Change Over the Eastern Mediterranean)
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Observation-Based Ozone Formation Rules by Gradient Boosting Decision Trees Model in Typical Chemical Industrial Parks
by
Nana Cheng, Deji Jing, Zhenyu Gu, Xingnong Cai, Zhanhong Shi, Sujing Li, Liang Chen, Wei Li and Qiaoli Wang
Atmosphere 2024, 15(5), 600; https://doi.org/10.3390/atmos15050600 - 14 May 2024
Abstract
Ozone pollution in chemical industrial parks is severe and complicated and is significantly influenced by pollutant emissions and meteorological parameters. In this study, we innovatively investigated the formation rules of ozone by using observation-based analyses and a gradient-boosting decision tree (GBDT) model, focusing
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Ozone pollution in chemical industrial parks is severe and complicated and is significantly influenced by pollutant emissions and meteorological parameters. In this study, we innovatively investigated the formation rules of ozone by using observation-based analyses and a gradient-boosting decision tree (GBDT) model, focusing on a typical chemical industrial park located in the Yangtze River Delta of China. The results revealed that ozone concentration was positively correlated with temperature while negatively correlated with NO2 concentration and relative humidity (RH). Ozone pollution was predominantly observed from April to October (M4–10). The optimized GBDT model was subsequently utilized to establish a specific and quantifiable relationship between each single dominant impact factor (RH, NO2, temperature, and PM2.5) and ozone within a complex and uncertain multi-factor context during M4–10. Detailed discussions were conducted on the reaction rate of ozone-related to different levels of RH and temperature. The accumulation of ozone was favored by high temperature and low RH, with the maximum ozone concentration observed at the RH of 50% and the temperature of 35 °C. The NO2-O3 change curve exhibited distinct phases, including a period of stability, gradual increase, rapid increase, and equilibrium. During the second and third periods, the ratio of ozone production to NO2 consumption was 0.10 and 2.73, respectively. Furthermore, there was a non-monotonic relationship between variations in ozone concentration and PM2.5 concentration. Hence, it is imperative to implement fine control strategies in the park, such as adopting seasonal production strategies, implementing targeted measures for controlling NOx and active VOCs, and employing special control methods during periods of high temperature. This study provides aid in achieving effective management of localized ozone pollution and ensuring compliance with air quality standards.
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(This article belongs to the Special Issue Advances in Source Tracing and the Control of Ozone and Its Precursors)
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Spatiotemporal Characteristics and Rainfall Thresholds of Geological Landslide Disasters in ASEAN Countries
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Weiping Lu, Zhixiang Xiao, Yuhang Chen, Jingwen Sun and Feisheng Chen
Atmosphere 2024, 15(5), 599; https://doi.org/10.3390/atmos15050599 - 14 May 2024
Abstract
Drawing upon a comprehensive global database of landslides and utilizing high-resolution IMERG satellite precipitation data, this study investigates the spatial and temporal variations of landslide occurrences across the member states of the Association of Southeast Asian Nations (ASEAN). This study constructs a region-specific,
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Drawing upon a comprehensive global database of landslides and utilizing high-resolution IMERG satellite precipitation data, this study investigates the spatial and temporal variations of landslide occurrences across the member states of the Association of Southeast Asian Nations (ASEAN). This study constructs a region-specific, graded warning system by formulating an average effective intensity–duration (I–D) rainfall threshold curve for each ASEAN member. Examination of 1747 landslide events spanning from 2006 to 2018 illustrates a significant association between the frequency of landslides in ASEAN regions and the latitudinal movement of local precipitation bands. Incidences of landslides hit their lowest in March and April, while a surge is observed from October to January, correlating with the highest mortality rates. Geographical hotspots for landslide activity, characterized by substantial annual rainfall and constrained landmasses, include the Philippine archipelago, Indonesia’s Java Island, and the Malay Peninsula, each experiencing an average of over 2.5 landslides annually. Fatalities accompany approximately 41.4% of ASEAN landslide events, with the Philippines and Indonesia registering the most substantial numbers. Myanmar stands out for the proportion of large-scale landslide incidents, with an average casualty rate of 10.89 deaths per landslide, significantly surpassing other countries in the region. The I–D rainfall threshold curves indicate that the Philippines experienced the highest precipitation levels before landslide initiation, whereas Myanmar has the threshold set at a considerably lower level.
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(This article belongs to the Section Meteorology)
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Comprehensive Analysis of Temporal–Spatial Fusion from 1991 to 2023 Using Bibliometric Tools
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Jiawei Cui, Juan Li, Xingfa Gu, Wenhao Zhang, Dong Wang, Xiuling Sun, Yulin Zhan, Jian Yang, Yan Liu and Xiufeng Yang
Atmosphere 2024, 15(5), 598; https://doi.org/10.3390/atmos15050598 - 14 May 2024
Abstract
Due to budget and sensor technology constraints, a single sensor cannot simultaneously provide observational images with both a high spatial and temporal resolution. To solve the above problem, the spatiotemporal fusion (STF) method was proposed and proved to be an indispensable tool for
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Due to budget and sensor technology constraints, a single sensor cannot simultaneously provide observational images with both a high spatial and temporal resolution. To solve the above problem, the spatiotemporal fusion (STF) method was proposed and proved to be an indispensable tool for monitoring land surface dynamics. There are relatively few systematic reviews of the STF method. Bibliometrics is a valuable method for analyzing the scientific literature, but it has not yet been applied to the comprehensive analysis of the STF method. Therefore, in this paper, we use bibliometrics and scientific mapping to analyze the 2967 citation data from the Web of Science from 1991 to 2023 in a metrological manner, covering the themes of STF, data fusion, multi-temporal analysis, and spatial analysis. The results of the literature analysis reveal that the number of articles displays a slow to rapid increase during the study period, but decreases significantly in 2023. Research institutions in China (1059 papers) and the United States (432 papers) are the top two contributors in the field. The keywords “Sentinel”, “deep learning” (DL), and “LSTM” (Long Short-Term Memory) appeared most frequently in the past three years. In the future, remote sensing spatiotemporal fusion research can address more of the limitations of heterogeneous landscapes and climatic conditions to improve fused images’ accuracy.
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(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
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Study and Modelling of the Impact of June 2015 Geomagnetic Storms on the Brazilian Ionosphere
by
Oladayo O. Afolabi, Claudia Maria Nicoli Candido, Fabio Becker-Guedes and Christine Amory-Mazaudier
Atmosphere 2024, 15(5), 597; https://doi.org/10.3390/atmos15050597 - 14 May 2024
Abstract
This study investigated the impact of the June 2015 geomagnetic storms on the Brazilian equatorial and low-latitude ionosphere by analyzing various data sources, including solar wind parameters from the advanced compositional explorer satellite (ACE), global positioning satellite vertical total electron content (GPS-VTEC
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This study investigated the impact of the June 2015 geomagnetic storms on the Brazilian equatorial and low-latitude ionosphere by analyzing various data sources, including solar wind parameters from the advanced compositional explorer satellite (ACE), global positioning satellite vertical total electron content (GPS-VTEC), geomagnetic data, and validation of the SAMI2 model-VTEC with GPS-VTEC. The effect of geomagnetic disturbances on the Brazilian longitudinal sector was examined by applying multiresolution analysis (MRA) of the maximum overlap discrete wavelet transform (MODWT) to isolate the diurnal component of the disturbance dynamo (Ddyn), DP2 current fluctuations from the ionospheric electric current disturbance (Diono), and semblance cross-correlation wavelet analysis for local phase comparison between the Sq and Diono currents. Our findings revealed that the significant fluctuations in DP2 at the Brazilian equatorial stations (Belem, dip lat: −0.47° and Alta Floresta, dip lat: −3.75°) were influenced by IMF Bz oscillations; the equatorial electrojet also fluctuated in tandem with the DP2 currents, and dayside reconnection generated the field-aligned current that drove the DP2 current system. The short-lived positive ionospheric storm during the main phase on 22 June in the Southern Hemisphere in the Brazilian sector was caused by the interplay between the eastward prompt penetration of the magnetospheric convection electric field and the westward disturbance dynamo electric field. The negative ionospheric storms that occurred during the recovery phase from 23 to 29 June 2015, were attributed to the westward disturbance dynamo electric field, which caused the downward drift of the plasma to a lower height with a high recombination rate. The comparison between the SAMI2 model-VTEC and GPS-VTEC indicates that the SAMI2 model underestimated the VTEC within magnetic latitudes of −9° to −24° in the Brazilian longitudinal sector from 6 to 17 June 2015. However, it demonstrated satisfactory agreement with the GPS-VTEC within magnetic latitudes of −9° to 10° from 8 to 15 June 2015. Conversely, the SAMI2 model overestimated the VTEC between ±10° magnetic latitudes from 16 to 28 June 2015. The most substantial root mean square error (RMSE) values, notably 10.30 and 5.48 TECU, were recorded on 22 and 23 June 2015, coinciding with periods of intense geomagnetic disturbance.
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(This article belongs to the Section Upper Atmosphere)
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How Cloud Droplet Number Concentration Impacts Liquid Water Path and Precipitation in Marine Stratocumulus Clouds—A Satellite-Based Analysis Using Explainable Machine Learning
by
Lukas Zipfel, Hendrik Andersen, Daniel Peter Grosvenor and Jan Cermak
Atmosphere 2024, 15(5), 596; https://doi.org/10.3390/atmos15050596 - 14 May 2024
Abstract
Aerosol–cloud–precipitation interactions (ACI) are a known major cause of uncertainties in simulations of the future climate. An improved understanding of the in-cloud processes accompanying ACI could help in advancing their implementation in global climate models. This is especially the case for marine stratocumulus
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Aerosol–cloud–precipitation interactions (ACI) are a known major cause of uncertainties in simulations of the future climate. An improved understanding of the in-cloud processes accompanying ACI could help in advancing their implementation in global climate models. This is especially the case for marine stratocumulus clouds, which constitute the most common cloud type globally. In this work, a dataset composed of satellite observations and reanalysis data is used in explainable machine learning models to analyze the relationship between the cloud droplet number concentration ( ), cloud liquid water path (LWP), and the fraction of precipitating clouds (PF) in five distinct marine stratocumulus regions. This framework makes use of Shapley additive explanation (SHAP) values, allowing to isolate the impact of from other confounding factors, which proved to be very difficult in previous satellite-based studies. All regions display a decrease of PF and an increase in LWP with increasing , despite marked inter-regional differences in the distribution of . Polluted (high ) conditions are characterized by an increase of 12 gm−2 in LWP and a decrease of 0.13 in PF on average when compared to pristine (low ) conditions. The negative –PF relationship is stronger in high LWP conditions, while the positive –LWP relationship is amplified in precipitating clouds. These findings indicate that precipitation suppression plays an important role in MSC adjusting to aerosol-driven perturbations in .
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(This article belongs to the Special Issue Aerosol-Cloud Interactions in Marine Warm Clouds)
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Feasibility of Urban-Based Climate Change Adaptation Strategies in Urban Centers of Southwest Ethiopia: From Local Climate Action Perspective
by
Tesfaye Dessu Geleta, Diriba Korecha Dadi, Weyessa Garedew and Adefires Worku
Atmosphere 2024, 15(5), 595; https://doi.org/10.3390/atmos15050595 - 14 May 2024
Abstract
This study identified the practices of adaptation strategies to climate change in Jimma, Bedelle, Bonga, and Sokorru urban centers using a survey of 384 households, 55 key informant interviews, 4 focus group discussions, and field observations. A cross-sectional study design was employed from
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This study identified the practices of adaptation strategies to climate change in Jimma, Bedelle, Bonga, and Sokorru urban centers using a survey of 384 households, 55 key informant interviews, 4 focus group discussions, and field observations. A cross-sectional study design was employed from 2019 to 2021. The adaptive capacity of municipalities to reduce climate extreme events was rated as poor by the majority (51%), mostly reactive measures (76%). The climate hazards identified in four urban centers were riverine and flash floods, urban heat waves, landslides, and windstorms. The urban households practiced lifestyle modification, reduce paved surfaces, the use of air conditioner, planting trees, and multiple windows. The adaptation strategies practiced by municipalities include the relocation of prone areas, the support of basic amenities, the construction of protection walls, diversion ditches, the clearance of waterways and rivers, greenery, and park development. The adaptation actions were constrained by a lack of awareness, commitment, cooperation and coordination, adaptive capacity, and participation. Gray/physical infrastructures (costly but important) as adaptation actions were hampered by the low municipal capacity. We recommend that urban authorities should incorporate climate change adaptation strategies into urban planning and development proactively to ensure future resilient climate smart urban centers of southwest Ethiopia.
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(This article belongs to the Special Issue Sustainable Technologies in Landscape and Urban Planning Response to Climate Change (2nd Edition))
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Forecasting the Exceedances of PM2.5 in an Urban Area
by
Stavros-Andreas Logothetis, Georgios Kosmopoulos, Orestis Panagopoulos, Vasileios Salamalikis and Andreas Kazantzidis
Atmosphere 2024, 15(5), 594; https://doi.org/10.3390/atmos15050594 - 13 May 2024
Abstract
Particular matter (PM) constitutes one of the major air pollutants. Human exposure to fine PM (PM with a median diameter less than or equal to 2.5 μm, PM2.5) has many negative and diverse outcomes for human health, such as respiratory mortality,
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Particular matter (PM) constitutes one of the major air pollutants. Human exposure to fine PM (PM with a median diameter less than or equal to 2.5 μm, PM2.5) has many negative and diverse outcomes for human health, such as respiratory mortality, lung cancer, etc. Accurate air-quality forecasting on a regional scale enables local agencies to design and apply appropriate policies (e.g., meet specific emissions limitations) to tackle the problem of air pollution. Under this framework, low-cost sensors have recently emerged as a valuable tool, facilitating the spatiotemporal monitoring of air pollution on a local scale. In this study, we present a deep learning approach (long short-term memory, LSTM) to forecast the intra-day air pollution exceedances across urban and suburban areas. The PM2.5 data used in this study were collected from 12 well-calibrated low-cost sensors (Purple Air) located in the greater area of the Municipality of Thermi in Thessaloniki, Greece. The LSTM-based methodology implements PM2.5 data as well as auxiliary data, meteorological variables from the Copernicus Atmosphere Monitoring Service (CAMS), which is operated by ECMWF, and time variables related to local emissions to enhance the air pollution forecasting performance. The accuracy of the model forecasts reported adequate results, revealing a correlation coefficient between the measured PM2.5 and the LSTM forecast data ranging between 0.67 and 0.94 for all time horizons, with a decreasing trend as the time horizon increases. Regarding air pollution exceedances, the LSTM forecasting system can correctly capture more than 70.0% of the air pollution exceedance events in the study region. The latter findings highlight the model’s capabilities to correctly detect possible WHO threshold exceedances and provide valuable information regarding local air quality.
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(This article belongs to the Special Issue Urban Air Quality Modelling)
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COVID-19 Lockdown Air Pollution Reduction: Did It Impact the Number of COPD Hospitalizations?
by
Jovan Javorac, Dejan Živanović, Miroslav Ilić, Vesna Mijatović Jovin, Svetlana Stojkov, Mirjana Smuđa, Ivana Minaković, Bela Kolarš, Veljko Ćućuz and Marija Jevtić
Atmosphere 2024, 15(5), 593; https://doi.org/10.3390/atmos15050593 - 13 May 2024
Abstract
In addition to the detrimental health consequences, the early stages of the COVID-19 pandemic have yielded unforeseen benefits in terms of reducing air pollution emissions. This study investigated air pollution changes in Novi Sad, Serbia, during the COVID-19 lockdown (March–June 2020) and their
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In addition to the detrimental health consequences, the early stages of the COVID-19 pandemic have yielded unforeseen benefits in terms of reducing air pollution emissions. This study investigated air pollution changes in Novi Sad, Serbia, during the COVID-19 lockdown (March–June 2020) and their correlation with acute exacerbations of chronic obstructive pulmonary disease (AECOPD) hospitalizations. Using quasi-Poisson generalized linear models (GLM) and distributed lag non-linear models (DLNM), we examined the relationship between the number of AECOPD hospitalizations and the concentrations of selected air pollutants (PM10, PM2.5, SO2, and NO2) from March to June of 2019, 2020, and 2021. During the COVID-19 lockdown, significant reductions in most air pollutant concentrations and the number of AECOPD hospitalizations were observed. However, neither the study year nor its interaction with air pollutant concentration significantly predicted AECOPD hospitalizations (p > 0.05). The 95% confidence intervals of the relative risks for the occurrence of AECOPD hospitalizations at each increase in the examined air pollutant by 10 μg/m3 overlapped across years, suggesting consistent effects of air pollution on the risk of AECOPD hospitalizations pre-pandemic and during lockdown. In conclusion, reduced air pollution emissions during the COVID-19 lockdown did not lead to a statistically significant change in the number of AECOPD hospitalizations.
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(This article belongs to the Special Issue Exposure Assessment of Air Pollution (2nd Edition))
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A New Analytical Simulation Code of Acoustic-Gravity Waves of Seismic Origin and Rapid Co-Seismic Thermospheric Disturbance Energetics
by
Saul A. Sanchez and Esfhan A. Kherani
Atmosphere 2024, 15(5), 592; https://doi.org/10.3390/atmos15050592 - 13 May 2024
Abstract
A recent study the detection of coseismic ionospheric disturbances or ionoquakes less than 400 s from the earthquake’s onset. The study also associates these rapid ionoquakes with the seismo-atmosphere–ionosphere (SAI) coupling mechanism energized by acoustic-gravity waves (AGWs) and the subsequent formation of coseismic
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A recent study the detection of coseismic ionospheric disturbances or ionoquakes less than 400 s from the earthquake’s onset. The study also associates these rapid ionoquakes with the seismo-atmosphere–ionosphere (SAI) coupling mechanism energized by acoustic-gravity waves (AGWs) and the subsequent formation of coseismic thermospheric disturbances (CSTDs). The present study outlines a new analytical simulation code for AGWs that resolves the governing equations in the time–altitude and wavenumber domain and confirms the rapid arrival of AGWs in the thermosphere (earlier than the estimated arrival time from the ray-tracing simulation). The rapid arrivals of AGWs are associated with long wavelengths that connect to thermospheric altitudes and propagate with thermospheric sound speeds, avoiding averaging effects from the lower atmosphere. The fast simulation traces the rapid arrival of AGWs in the thermosphere and produces rapid CSTDs within 250–300 s from the earthquake’s onset. The simulation time is much shorter than the formation time of near-field CSTDs, a scenario favorable for the forecasting of CSTDs before observations of ionoquakes. In essence, the fast simulation offers an alternative tool for tracking the evolution of CSTDs.
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(This article belongs to the Special Issue Waves and Variability in Terrestrial and Planetary Atmospheres)
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