-
Oxygen Isotope Fractionation Due to Non-Thermal Escape of Hot O from the Atmosphere of Mars
-
TraPSA-Web: Trajectory-Ensemble Toolkit for Atmospheric Pollutant Potential Source Identification
-
Indoor Radon Surveying and Mitigation in the Case-Study of Celleno Town (Central Italy)
-
Important Contribution to Aerosol Oxidative Potential from Residential Solid Fuel Burning in Central Ireland
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 journals for Atmosphere include: Meteorology and Aerobiology.
Impact Factor:
2.5 (2023);
5-Year Impact Factor:
2.6 (2023)
Latest Articles
Carbonyl Sulfide (COS) in Terrestrial Ecosystem: What We Know and What We Do Not
Atmosphere 2024, 15(7), 778; https://doi.org/10.3390/atmos15070778 (registering DOI) - 28 Jun 2024
Abstract
Over the past six decades, carbonyl sulfide (COS) in terrestrial ecosystems has been extensively studied, with research focusing on exploring its ecological and environmental effects, estimating source–sink volume, and identifying influencing factors. The global terrestrial COS sink has been estimated to be about
[...] Read more.
Over the past six decades, carbonyl sulfide (COS) in terrestrial ecosystems has been extensively studied, with research focusing on exploring its ecological and environmental effects, estimating source–sink volume, and identifying influencing factors. The global terrestrial COS sink has been estimated to be about 1.194–1.721 Tg a−1, with the terrestrial sink induced by plants and soils 0.50–1.20 Tg a−1, accounting for 41%–69% of the total. Hence, the role of plants and soils as COS sinks has been extensively explored. Now we know that factors such as the activity of carbonic anhydrase (CA), leaf structural traits, soil microbial activity, and environmental factors play significant roles in the COS budget. Developments in observational techniques have also made important contributions to the COS budget. This paper provides an overview of the research progress made on COS based on a comprehensive review of the literature. Then, it highlights the current research hotspots and issues requiring further exploration. For instance, it has been demonstrated that there are still significant uncertainties in the estimation of COS sources and sinks, emphasizing the need for further exploration of COS measuring techniques. This review aims to provide comprehensive guidance for COS research in terrestrial ecosystems.
Full article
(This article belongs to the Special Issue Carbon Emission and Carbon Neutrality in China)
Open AccessArticle
Trend Analysis and Spatial Source Attribution of Surface Ozone in Chaozhou, China
by
Zhongwen Huang, Lei Tong, Xuchu Zhu, Junxiao Su, Shaoyun Lu and Hang Xiao
Atmosphere 2024, 15(7), 777; https://doi.org/10.3390/atmos15070777 (registering DOI) - 28 Jun 2024
Abstract
Surface ozone (O3), a critical air pollutant, poses significant challenges in urban environments, as exemplified by the city of Chaozhou in southeastern China. This study employs a novel combination of trend analysis and spatial source attribution techniques to evaluate the long-term
[...] Read more.
Surface ozone (O3), a critical air pollutant, poses significant challenges in urban environments, as exemplified by the city of Chaozhou in southeastern China. This study employs a novel combination of trend analysis and spatial source attribution techniques to evaluate the long-term dynamics of surface ozone and identify its sources. Utilizing the Kolmogorov–Zurbenko (KZ) filter and percentile regression, we analyzed the temporal trends of daily maximum 8 h moving average ozone (MDA8 O3) concentrations from 2014 to 2023. Our analysis revealed a general long-term downward trend in MDA8 O3 values alongside notable monthly fluctuations, with peak concentrations typically occurring in October and April. Additionally, the percentile regression analysis demonstrated a significant downward trend in MDA8 O3 concentrations across nearly all percentiles, with larger decline rates at higher percentiles, highlighting the effectiveness of local and regional O3 management strategies in Chaozhou. The changes in MDA8 O3 concentrations were mainly influenced by the short-term component, contributing 62.2%, while the contribution of the long-term fraction is relatively small. This suggests a significant influence of immediate meteorological conditions and transient pollution events on local O3 levels. To further elucidate the origins of high O3 concentrations, trajectory cluster analysis, trajectory sector analysis (TSA), and potential source contribution function (PSCF) analysis were conducted. The trajectory cluster analysis revealed that the northeast air mass was the main transport air mass in Chaozhou during the study period, accounting for 39.1% of occurrences. The northeast cluster C with medium-distance trajectories corresponds to higher concentration of O3, which may be the main transport pathway of O3 pollution in Chaozhou. TSA corroborates these findings, with northeast sectors 1, 2, and 3 accounting for 50.3% of trajectory residence time and contributing 52.2% to O₃ levels in Chaozhou. PSCF results further indicate potential high O₃ sources from the northeast, especially in autumn. This comprehensive analysis suggests that Chaozhou’s elevated O3 levels are influenced by both regional transport from the northeast and local emissions. These findings offer crucial insights into the temporal dynamics of surface O3 in Chaozhou, paving the way for more effective and targeted air quality management strategies.
Full article
(This article belongs to the Special Issue Ozone Pollution and Effects in China)
Open AccessArticle
Can Bayesian Networks Improve Ground-Strike Point Classification?
by
Wandile Lesejane, Hugh G. P. Hunt, Carina Schumann and Ritesh Ajoodha
Atmosphere 2024, 15(7), 776; https://doi.org/10.3390/atmos15070776 (registering DOI) - 28 Jun 2024
Abstract
Studying cloud-to-ground lightning strokes and ground-strike points provides an alternative method of lightning mapping for lightning risk assessment. Various k-means algorithms have been used to verify the ground-strike points from lightning locating systems, producing results with room for improvement. This paper proposes using
[...] Read more.
Studying cloud-to-ground lightning strokes and ground-strike points provides an alternative method of lightning mapping for lightning risk assessment. Various k-means algorithms have been used to verify the ground-strike points from lightning locating systems, producing results with room for improvement. This paper proposes using Bayesian networks (BNs), a model not previously used for this purpose, to classify lightning ground-strike points. A Bayesian network is a probabilistic graphical model that uses Bayes’ theorem to represent the conditional dependencies of variables. The networks created for this research were trained from the data using a score-based structure-learning procedure and the Bayesian information criterion score function. The models were evaluated using confusion matrices and kappa indices and produced accuracy values ranging from 86% to 94% and kappa indices of up to 0.76. While BN models do not outperform k-means algorithms, they offer an alternative by not requiring predetermined distances. However, the easy implementation of the k-means approach means that no significant gain is made by implementing the more complex Bayesian network approach.
Full article
(This article belongs to the Special Issue Recent Advances in Lightning Research)
Open AccessArticle
WRF-Chem Modeling of Tropospheric Ozone in the Coastal Cities of the Gulf of Finland
by
Georgii Nerobelov, Yana Virolainen, Dmitry Ionov, Alexander Polyakov and Eugene Rozanov
Atmosphere 2024, 15(7), 775; https://doi.org/10.3390/atmos15070775 (registering DOI) - 28 Jun 2024
Abstract
Ozone in the troposphere is a pollutant and greenhouse gas. Atmospheric models can add valuable information to observations for studying the spatial and temporal variations in tropospheric ozone content. The present study is intended to evaluate the variability in tropospheric ozone and its
[...] Read more.
Ozone in the troposphere is a pollutant and greenhouse gas. Atmospheric models can add valuable information to observations for studying the spatial and temporal variations in tropospheric ozone content. The present study is intended to evaluate the variability in tropospheric ozone and its precursors near the Gulf of Finland with a focus on St. Petersburg (Russia) and Helsinki (Finland) in 2016–2019, using the WRF-Chem 3-D numerical model with a spatial resolution of 10 km, together with observations. The diurnal cycle of the near-surface ozone concentrations (NSOCs) in both cities is caused by the variability in NO2 emissions, planetary boundary layer height, and local meteorological conditions. The seasonal variations in NSOCs and tropospheric ozone content (TrOC) are caused by the variability in total ozone content and in ozone formation in the troposphere. The model reveals a VOC-limited regime in the ~0–1 km layer around St. Petersburg, Helsinki, and the Gulf of Finland and a pronounced NOx-limited regime in the 0–2 km layer in the forests of southern Finland, Karelia, some Russian regions, and the Baltic countries in July. The WRF-Chem model overestimates the measured NSOCs by 10.7–43.5% and the TrOC by 7–10.4%. The observed differences are mainly caused by the errors in chemical boundary conditions and emissions of ozone precursors and by the coarse spatial resolution of the modeling.
Full article
(This article belongs to the Special Issue Measurement and Variability of Atmospheric Ozone)
►▼
Show Figures
![](https://pub.mdpi-res.com/atmosphere/atmosphere-15-00775/article_deploy/html/images/atmosphere-15-00775-g001-550.jpg?1719574086)
Figure 1
Open AccessArticle
GIS-Based Integrated Multi-Hazard Vulnerability Assessment in Makedonska Kamenica Municipality, North Macedonia
by
Bojana Aleksova, Ivica Milevski, Slavoljub Dragićević and Tin Lukić
Atmosphere 2024, 15(7), 774; https://doi.org/10.3390/atmos15070774 (registering DOI) - 28 Jun 2024
Abstract
This study presents a comprehensive analysis of natural hazard susceptibility in the Makedonska Kamenica municipality of North Macedonia, encompassing erosion assessment, landslides, flash floods, and forest fire vulnerability. Employing advanced GIS and remote sensing (RS) methodologies, hazard models were meticulously developed and integrated
[...] Read more.
This study presents a comprehensive analysis of natural hazard susceptibility in the Makedonska Kamenica municipality of North Macedonia, encompassing erosion assessment, landslides, flash floods, and forest fire vulnerability. Employing advanced GIS and remote sensing (RS) methodologies, hazard models were meticulously developed and integrated to discern areas facing concurrent vulnerabilities. Findings unveil substantial vulnerabilities prevalent across the area, notably along steep terrain gradients, river valleys, and deforested landscapes. Erosion assessment reveals elevated rates, with a mean erosion coefficient (Z) of 0.61 and an annual erosion production of 182,712.9 m3, equivalent to a specific erosion rate of 961.6 m3/km2/year. Landslide susceptibility analysis identifies 31.8% of the municipality exhibiting a very high probability of landslides, while flash flood susceptibility models depict 3.3% of the area prone to very high flash flood potential. Forest fire susceptibility mapping emphasizes slightly less than one-third of the municipality’s forested area is highly or very highly susceptible to fires. Integration of these hazard models elucidates multi-hazard zones, revealing that 11.0% of the municipality’s territory faces concurrent vulnerabilities from excessive erosion, landslides, flash floods, and forest fires. These zones are predominantly located in upstream areas, valleys of river tributaries, and the estuary region. The identification of multi-hazard zones underscores the critical need for targeted preventive measures and robust land management strategies to mitigate potential disasters and safeguard both human infrastructure and natural ecosystems. Recommendations include the implementation of enhanced monitoring systems, validation methodologies, and community engagement initiatives to bolster hazard preparedness and response capabilities effectively.
Full article
(This article belongs to the Section Biosphere/Hydrosphere/Land–Atmosphere Interactions)
►▼
Show Figures
![](https://pub.mdpi-res.com/atmosphere/atmosphere-15-00774/article_deploy/html/images/atmosphere-15-00774-g001-550.jpg?1719570444)
Figure 1
Open AccessArticle
Evaluation of Emission Factors for Particulate Matter and NO2 from Road Transport in Sofia, Bulgaria
by
Margret Velizarova, Reneta Dimitrova, Petar O. Hristov, Angel Burov, Danail Brezov, Elena Hristova and Orlin Gueorguiev
Atmosphere 2024, 15(7), 773; https://doi.org/10.3390/atmos15070773 - 28 Jun 2024
Abstract
Traffic-related air pollution has a significant impact on the concentration of particulate matter (PM) and nitrogen oxides (NOx) in urban areas, but there are many uncertainties associated with the modeling of PM concentration due to non-exhaust emissions. Bulgarian weather, road surfaces
[...] Read more.
Traffic-related air pollution has a significant impact on the concentration of particulate matter (PM) and nitrogen oxides (NOx) in urban areas, but there are many uncertainties associated with the modeling of PM concentration due to non-exhaust emissions. Bulgarian weather, road surfaces and traffic conditions differ significantly from the UK’s and other EU countries’ averages, which underpin many assumptions in established models. The hypothesis is that the emission factors differ from those used to calculate traffic emissions using the EMIT model. The objective of this work is to adjust the emissions for PM and the relationship between the fractions of NOx and PM using the hourly mean concentrations from road transport and urban background automatic air quality stations in Sofia, Bulgaria. Various already-published and newly developed methods are applied to local observations to derive functions and relations that better represent Bulgarian road and traffic conditions. The ADMS-Urban model is validated and evaluated by comparing pollutant concentrations from simulations using original and adjusted emissions, showing an improvement in results after applying functions and relationships derived from local observations. This work is part of our efforts to improve air quality modeling in urban areas in Bulgaria.
Full article
(This article belongs to the Special Issue Air Pollution in Urban and Regional Level: Sources, Sinks and Transportation (3rd Edition))
►▼
Show Figures
![](https://pub.mdpi-res.com/atmosphere/atmosphere-15-00773/article_deploy/html/images/atmosphere-15-00773-g001-550.jpg?1719567034)
Figure 1
Open AccessArticle
Optimization and Application of Analytical Assays for the Determination of Oxidative Potential of Outdoor and Indoor Particulate Matter
by
Andrea Bergomi, Elena Carrara, Elisa Festa, Cristina Colombi, Eleonora Cuccia, Beatrice Biffi, Valeria Comite and Paola Fermo
Atmosphere 2024, 15(7), 772; https://doi.org/10.3390/atmos15070772 - 28 Jun 2024
Abstract
Recent studies indicate that mass concentration alone is not the best parameter to assess the toxicity and the health effects of particulate matter (PM). Indeed, the chemical composition of the particles plays an important role, and oxidative potential (OP) measurements are being proposed
[...] Read more.
Recent studies indicate that mass concentration alone is not the best parameter to assess the toxicity and the health effects of particulate matter (PM). Indeed, the chemical composition of the particles plays an important role, and oxidative potential (OP) measurements are being proposed as an alternative way to assess toxicity. The European Union (EU) is currently proposing a draft of the new air quality directive which includes OP measurements but does not specify the methods and/or protocols of analysis. In this light, the purpose of this study was to evaluate the feasibility of two literature assays, namely ascorbic acid (AA) and dithiothreitol (DTT), for routine PM analysis by testing urban PM filters from a one-year sampling campaign conducted by ARPA Lombardia. Indoor PM samples were also tested to emphasize the importance of monitoring closed spaces in which people spend most of their time. Following the optimization of the DTT assay, both methods proved to be suitable for large-scale PM analysis. The results show that the oxidative strength of urban PM is constant throughout the year for the outdoor samples (OPAA: 0.067–0.39 nmol min−1 m−3; OPDTT: 0.033–0.109 nmol min−1 m−3), indicating the need for routine OP monitoring. Instead, indoor areas were characterized by particles with a lower oxidative capacity (OPAA: 5.40–24 pmol min−1 m−3; OPDTT: 9.7–32 pmol min−1 m−3), driven both by lower concentrations and a different chemical composition. All the data collected highlight the need to add this parameter as part of the chemical characterization of PM, moving in the same direction as the new EU air quality directive.
Full article
(This article belongs to the Section Air Quality and Human Health)
►▼
Show Figures
![](https://pub.mdpi-res.com/atmosphere/atmosphere-15-00772/article_deploy/html/images/atmosphere-15-00772-g001-550.jpg?1719565953)
Figure 1
Open AccessArticle
Short-Term Exposure to Ambient Air Pollution and Schizophrenia Hospitalization: A Case-Crossover Study in Jingmen, China
by
Yuwei Zhou, Jixing Yang, Jingjing Zhang, Yixiang Wang, Jiajun Shen, Yalin Zhang, Yuxi Tan, Yunquan Zhang and Chengyang Hu
Atmosphere 2024, 15(7), 771; https://doi.org/10.3390/atmos15070771 - 27 Jun 2024
Abstract
The impact of short-term exposure to air pollutants on the morbidity of schizophrenia, particularly in low- and middle-income countries, remains inadequately explored. The objective of this research was to investigate the relationship between short-term exposure to ambient air pollutants and the risk of
[...] Read more.
The impact of short-term exposure to air pollutants on the morbidity of schizophrenia, particularly in low- and middle-income countries, remains inadequately explored. The objective of this research was to investigate the relationship between short-term exposure to ambient air pollutants and the risk of schizophrenia hospitalization in Jingmen, China. We performed a time-stratified case-crossover study using daily records of hospital admissions due to schizophrenia in Jingmen Mental Health Center from 2015 to 2017. Environmental exposures to air pollutants and meteorological conditions on case and control days were estimated on the basis of measurements from ground monitoring stations. To investigate the relationship between short-term exposure to ambient air pollutants and the risk of hospitalization for schizophrenia, a conditional logistic regression model was employed. We performed subgroup analyses stratified according to sex, age groups, and season. In total, 4079 schizophrenia hospitalizations were recorded during the designated period. Increased risk of schizophrenia was merely associated with short-term exposure to SO2 and NO2. The estimated odds per interquartile range (IQR) increase in exposure was 1.112 (95% confidence interval (CI): 1.033, 1.196) for SO2 (IQR = 12 µg/m3) and 1.112 (95% CI: 1.033, 1.197) for NO2 (IQR = 18 µg/m3) on lag-0 day. Greater air pollution-schizophrenia associations were observed among middle-aged and older adults (over 45 years of age) and during the cold season. This study added case-crossover evidence indicating that short-term exposure to ambient air pollution, specifically SO2 and NO2, is linked to a higher risk of hospital admissions for schizophrenia. These findings contribute to a better understanding of the detrimental effects of air pollution on neuropsychiatric health conditions.
Full article
(This article belongs to the Special Issue Outdoor Air Pollution and Human Health (3rd Edition))
Open AccessArticle
Spatio–Temporal Evolution of Electric Field, Magnetic Field and Thermal Infrared Remote Sensing Associated with the 2021 Mw7.3 Maduo Earthquake in China
by
Muping Yang, Xuemin Zhang, Meijiao Zhong, Yufan Guo, Geng Qian, Jiang Liu, Chao Yuan, Zihao Li, Shuting Wang, Lina Zhai, Tongxia Li and Xuhui Shen
Atmosphere 2024, 15(7), 770; https://doi.org/10.3390/atmos15070770 - 27 Jun 2024
Abstract
This study presents the spatio–temporal evolution of the electric and magnetic fields recorded by the China Seismo–Electromagnetic Satellite (CSES) and the thermal infrared remote sensing data observed by the Chinese stationary meteorological satellites Feng Yun–2G (FY–2G) associated with the 2021 Mw7.3 Maduo earthquake.
[...] Read more.
This study presents the spatio–temporal evolution of the electric and magnetic fields recorded by the China Seismo–Electromagnetic Satellite (CSES) and the thermal infrared remote sensing data observed by the Chinese stationary meteorological satellites Feng Yun–2G (FY–2G) associated with the 2021 Mw7.3 Maduo earthquake. Specifically, we analyzed the power spectrum density (PSD) data of the electric field in the extremely low frequency (ELF) band, the geomagnetic east–west vector data, and the temperature of brightness blackbody (TBB) data to investigate the spatio–temporal evolution characteristics under quiet space weather conditions (Dst > −30 nT and Kp < 3). Results showed that (1) the TBB radiation began to increase notably along the northern fault of the epicenter ~1.5 months prior to the occurrence of the earthquake. It achieved its maximum intensity on 17 May, and the earthquake occurred as the anomalies decreased. (2) The PSD in the 371 Hz–500 Hz and 700 Hz–871 Hz bands exhibited anomaly perturbations near the epicenter and its magnetic conjugate area on May 17, with particularly notable perturbations observed in the latter. The anomaly perturbations began to occur ~1 month before the earthquake, and the earthquake occurred as the anomalies decreased. (3) Both the magnetic –east–west component vector data and the ion velocity Vx data exhibited anomaly perturbations near the epicenter and the magnetic conjugate area on 11 May and 16 May. (4) The anomaly perturbations in the thermal infrared TBB data, CSES electric field, and magnetic field data all occurred within a consistent perturbation time period and spatial proximity. We also conducted an investigation into the timing, location, and potential causes of the anomaly perturbations using the Vx ion velocity data with magnetic field –east–west component vector data, as well as the horizontal –north–south and vertical component PSD data of the electric field with the magnetic field –east–west component vector data. There may be both chemical and electromagnetic wave propagation models for the “lithosphere—atmosphere—ionosphere” coupling (LAIC) mechanism of the Maduo earthquake.
Full article
(This article belongs to the Special Issue Ionospheric Sounding for Identification of Pre-seismic Activity)
Open AccessArticle
Trace Extraction and Repair of the F Layer from Pictorial Ionograms
by
Jiayi Wang, Lei Qiao, Chunxiao Yan, Zhaoyang Qiu and Kejie Wang
Atmosphere 2024, 15(7), 769; https://doi.org/10.3390/atmos15070769 - 27 Jun 2024
Abstract
Publicly available ionograms are often in the form of pictures. This paper proposes a novel algorithm for extracting and repairing the F layer traces from pictorial ionograms. Extensive efforts have been invested in ionogram autoscaling and critical parameter identification to improve the efficiency
[...] Read more.
Publicly available ionograms are often in the form of pictures. This paper proposes a novel algorithm for extracting and repairing the F layer traces from pictorial ionograms. Extensive efforts have been invested in ionogram autoscaling and critical parameter identification to improve the efficiency of scaling algorithms. To obtain the parameters of the F layer automatically, it is necessary to accurately extract the F layer trace. However, research on F layer trace extraction with repair is relatively limited. The method employed in this study makes full use of the characteristics of different types of echoes on the ionograms, and the procedure includes noise preprocessing, coupling noise processing, and trace repair. To enhance the applicability of the repair, two different automatic filling algorithms are adopted to repair the F layer trace. The aim of this paper is to present an adaptive algorithm to automatically extract and repair F layer traces from different pictorial ionograms. The results of Hainan Fuke ionograms illustrate the reliability of the F layer trace extraction and trace repair.
Full article
(This article belongs to the Section Upper Atmosphere)
►▼
Show Figures
![](https://pub.mdpi-res.com/atmosphere/atmosphere-15-00769/article_deploy/html/images/atmosphere-15-00769-g001-550.jpg?1719496453)
Figure 1
Open AccessArticle
Critical Drought Characteristics: A New Concept Based on Dynamic Time Period Scenarios
by
Ahmad Abu Arra, Mehmet Emin Birpınar, Şükrü Ayhan Gazioğlu and Eyüp Şişman
Atmosphere 2024, 15(7), 768; https://doi.org/10.3390/atmos15070768 - 27 Jun 2024
Abstract
In research on monitoring drought events, analysis is often carried out using a single period as a reference. On the other hand, changing this default period in drought calculations causes the drought index values obtained from research to differ. As a gap in
[...] Read more.
In research on monitoring drought events, analysis is often carried out using a single period as a reference. On the other hand, changing this default period in drought calculations causes the drought index values obtained from research to differ. As a gap in the literature, this point highlights the necessity of investigating the effect of various time periods on drought characteristics. It underscores the need to propose a new concept and methodology to address this gap effectively. This research aims to analyze critical drought characteristics through dynamic time period scenarios. For the first time in the literature, drought indices and potential and critical characteristics were analyzed for various (dynamic) time periods. Drought analysis was carried out for 13 time period scenarios with 10-year intervals from a meteorological station in Durham (1872–2021) by changing the initial time condition using the Standardized Precipitation Index (SPI). The results showed that in addition to the similarities, there are significant differences between drought characteristics. For example, in some time period scenarios, a drought event was recorded during a specific period, while in other scenarios (S5–S7, S10–S13), no drought was detected during the same period, like in SPI 1. Additionally, for SPI 12, the drought duration varied significantly, lasting between 20 and 29 months, and for SPI 6, the drought duration varied between 3 and 13 months. Regarding the intensity, SPI 1 ranged between −0.89 and −1.33, indicating a 33% difference, and the SPI 3 intensity ranged between −1.08 and −1.91, indicating a 50% increase in intensity. This research significantly contributes to the field by providing a novel approach using dynamic time period scenarios to determine critical drought characteristics, offering valuable insights for water resource management, drought mitigation planning, and design purposes.
Full article
(This article belongs to the Special Issue Drought Monitoring, Prediction and Impacts)
Open AccessArticle
Investigation and Validation of Short-Wave Scattering in the Anisotropic Ionosphere under a Geomagnetic Field
by
Zhigang Zhang, Jingyi She, Hongwei Fu, Lin Zhao and Shengyun Ji
Atmosphere 2024, 15(7), 767; https://doi.org/10.3390/atmos15070767 - 27 Jun 2024
Abstract
Short-wave communication, operating within the frequency range of 3–30 MHz, is extensively employed for long-distance communication because of its extended propagation range and robustness. The ionosphere undergoes complex transformations when influenced by the geomagnetic field, evolving into an uneven and anisotropic electromagnetic medium.
[...] Read more.
Short-wave communication, operating within the frequency range of 3–30 MHz, is extensively employed for long-distance communication because of its extended propagation range and robustness. The ionosphere undergoes complex transformations when influenced by the geomagnetic field, evolving into an uneven and anisotropic electromagnetic medium. This complex property makes the transmission of electromagnetic fields within the ionosphere extremely complex, posing significant challenges for accurately evaluating electromagnetic scattering phenomena. To address the aforementioned challenges, this paper proposes a new method for calculating short-wave ionospheric scattering based on a complex anisotropic multilayer medium transmission matrix. Firstly, by utilizing the characteristic changes of ionospheric electron density with height, the ionization layer is divided into multiple horizontal thin layers, each with an approximately uniform electron density, forming a multilayer horizontal anisotropic structure. Subsequently, the scattering characteristics of electromagnetic waves in the ionosphere were calculated using the transmission matrix approach. The results calculated using this method are consistent with actual measurement values and superior to traditional short-wave ionospheric transmission calculation methods.
Full article
(This article belongs to the Special Issue Intelligent Modeling of the Ionosphere and Troposphere for Radio Application)
Open AccessArticle
Evaluation of the Zenith Tropospheric Delay (ZTD) Derived from VMF3_FC and VMF3_OP Products Based on the CMONOC Data
by
Haoran Zhang, Liang Chen, Fei Yang, Jingge Ma, Junya Zhang, Wenyu Sun and Shiqi Xu
Atmosphere 2024, 15(7), 766; https://doi.org/10.3390/atmos15070766 - 27 Jun 2024
Abstract
Prior tropospheric information, especially zenith tropospheric delay (ZTD), is particularly important in GNSS data processing. The two types of ZTD models, those that require and do not require meteorological parameters, are the most commonly used models, whether the non-difference or double-difference mode is
[...] Read more.
Prior tropospheric information, especially zenith tropospheric delay (ZTD), is particularly important in GNSS data processing. The two types of ZTD models, those that require and do not require meteorological parameters, are the most commonly used models, whether the non-difference or double-difference mode is applied. To improve the accuracy of prior tropospheric information, the Vienna Mapping Functions (VMFs) data server provides a gridded set of global tropospheric products based on the ray-tracing technique using Numerical Weather Models (NWMs). Note that two types of gridded tropospheric products are provided: the VMF3_OP for the post-processing applications and the VMF3_FC for real-time applications. To explore the accuracy and adaptability of these two grid products, a comprehensive analysis and discussion were conducted in this study using the ZTD data from 255 stations of the Crustal Movement Observation Network of China (CMONOC) as references. The numerical results indicate that both VMF3_FC and VMF3_OP exhibit high accuracy, with RMSE/Bias values of 17.53/2.25 mm and 14.62/2.67 mm, respectively. Both products displayed a temporal trend, with larger RMSE values occurring in summer and smaller values in winter, along with a spatial trend of higher values in the southeast of China and lower values in the northwest of China. Additionally, VMF3_OP demonstrated superior performance to VMF3_FC, with smaller RMSE values for each month and each hour. For the RMSE difference between these two products, 108 stations had a difference of more than 3 mm, and the number of stations with a difference exceeding 1 mm reached 217. Moreover, the difference was more significant in the southeast than in the northwest. This study contributes to the understanding of the differences between the two precision products, aiding in the selection of suitable ZTD products based on specific requirements.
Full article
(This article belongs to the Special Issue GNSS Meteorology: Algorithm, Modelling, Assessment and Application)
Open AccessArticle
Assessing Carbon Sink Capacity in Coal Mining Areas: A Case Study from Taiyuan City, China
by
Fan Chen, Yang Liu, Jinkai Guo, He Bai, Zhitao Wu, Yang Liu and Ruijin Li
Atmosphere 2024, 15(7), 765; https://doi.org/10.3390/atmos15070765 - 27 Jun 2024
Abstract
Climate warming and air pollution are atmospheric environmental problems that have aroused broad concern worldwide. Greenhouse gas emissions are the main cause of global warming. In addition to reducing carbon emissions, increasing carbon sink capacity and improving environmental quality are essential for building
[...] Read more.
Climate warming and air pollution are atmospheric environmental problems that have aroused broad concern worldwide. Greenhouse gas emissions are the main cause of global warming. In addition to reducing carbon emissions, increasing carbon sink capacity and improving environmental quality are essential for building green and low-carbon enterprises under carbon peak and carbon neutrality goals. Currently, the research on the methods and application of carbon sink capacity assessment in coal mining enterprises is limited. Given this, this study estimated the carbon absorption, carbon storage, and net ecosystem productivity of a typical coal mining area in Taiyuan City, China, and compared the characteristics and applicability of the three methods. The results showed the following: (1) The total carbon absorption (carbon sink) of the mining area in 2021 was 117.39 t, the primary source of which is forest land. (2) The total carbon storage in the mining area in 2021 was 29,561.96 t. From different land use types, the carbon storage in the mining area mainly came from forest land (27,867.73 t); from the perspective of carbon pool, soil carbon storage (21,970.96 t) had the most significant contribution to the carbon storage of mining areas. (3) The net ecosystem productivity of the mining area in 2021 was 781.97 g/(m2·a), indicating that the ecosystem of the mining area was a carbon sink. (4) The three estimation methods differed in the current case. The estimation method for carbon absorption is the simplest, and the results are the most intuitive. The estimation method for net ecosystem productivity is the most complex. The carbon sink estimation via carbon storage needs to collect two years of data. Enterprises should assess the carbon sink capacity of mining areas based on existing conditions and data. This study proposes methods for estimating carbon sink capacity in mining areas, which have positive practical significance for the low-carbon green development of coal mine enterprises.
Full article
(This article belongs to the Special Issue Urban Air Pollution Control and Low-Carbon Development)
►▼
Show Figures
![](https://pub.mdpi-res.com/atmosphere/atmosphere-15-00765/article_deploy/html/images/atmosphere-15-00765-g001-550.jpg?1719491677)
Figure 1
Open AccessArticle
Evaluating the Conservation Status and Effectiveness of Multi-Type Protected Areas for Carbon Sequestration in the Loess Plateau, China
by
Sony Lama, Jingjing Zhang and Xiaofeng Luan
Atmosphere 2024, 15(7), 764; https://doi.org/10.3390/atmos15070764 - 27 Jun 2024
Abstract
Evaluating the conservation effectiveness of multiple types of protected areas (PAs) on carbon sequestration services can enhance the role of PAs in mitigating global warming. Here, we evaluated the conservation status and effectiveness of national parks, nature reserves, forest parks, geo-parks, and scenic
[...] Read more.
Evaluating the conservation effectiveness of multiple types of protected areas (PAs) on carbon sequestration services can enhance the role of PAs in mitigating global warming. Here, we evaluated the conservation status and effectiveness of national parks, nature reserves, forest parks, geo-parks, and scenic spots on carbon sequestration within the Loess Plateau throughout 2000–2020. The results show that all existing PA types have good representation and conservation effectiveness on carbon sequestration. Nature reserves are the most representative of carbon sequestration but are the least effective in protecting carbon sequestration and are the only ones that are weekly effective in protecting critical carbon sequestration. The main factors influencing these results are PA size, 2000 precipitation, slope, change rate of evapotranspiration, PA rank, and 2000 evapotranspiration. We suggest upgrading the critical carbon sequestration distribution areas in scenic spots, forest parks and geo-parks to national parks or nature reserves in the future and implementing appropriate protection and restoration measures in low carbon sequestration areas within grassland and wild plant nature reserves to help achieve the goal of carbon neutrality early.
Full article
(This article belongs to the Special Issue Urban and Regional Nitrogen Cycle and Risk Management)
►▼
Show Figures
![](https://pub.mdpi-res.com/atmosphere/atmosphere-15-00764/article_deploy/html/images/atmosphere-15-00764-g001-550.jpg?1719505649)
Figure 1
Open AccessArticle
IMERG in the Canadian Precipitation Analysis (CaPA) System for Winter Applications
by
Stéphane Bélair, Pei-Ning Feng, Franck Lespinas, Dikra Khedhaouiria, David Hudak, Daniel Michelson, Catherine Aubry, Florence Beaudry, Marco L. Carrera and Julie M. Thériault
Atmosphere 2024, 15(7), 763; https://doi.org/10.3390/atmos15070763 - 27 Jun 2024
Abstract
Several configurations of the Canadian Precipitation Analysis system (CaPA) currently produce precipitation analyses at Environment and Climate Change Canada (ECCC). To improve CaPA’s performance during the winter season, the impact of assimilating the IMERG V06 product (IMERG: Integrated Multi-satellitE Retrievals for GPM—Global Precipitation
[...] Read more.
Several configurations of the Canadian Precipitation Analysis system (CaPA) currently produce precipitation analyses at Environment and Climate Change Canada (ECCC). To improve CaPA’s performance during the winter season, the impact of assimilating the IMERG V06 product (IMERG: Integrated Multi-satellitE Retrievals for GPM—Global Precipitation Measurement mission) into CaPA is examined in this study. Tests are conducted with CaPA’s 10 km deterministic version, evaluated over Canada and the northern part of the United States (USA). Maps from a case study show that IMERG plays a contradictory role in the production of CaPA’s precipitation analyses for a synoptic-scale winter storm over North America’s eastern coast. While its contribution appears to be physically correct over southern portions of the meteorological system, and early in its intensification phase, IMERG displays unrealistic spatial structures over land later in the system’s life cycle when it is located over northern (colder) areas. Objective evaluation of CaPA’s analyses when IMERG is assimilated without any restrictions shows an overall decrease in precipitation, which has a mixed effect (positive and negative) on the bias indicators. But IMERG’s influence on the Equitable Threat Score (ETS), a measure of CaPA’s analyses accuracy, is clearly negative. Using IMERG’s quality index (QI) to filter out areas where it is less accurate improves CaPA’s objective evaluation, leading to better ETS versus the control experiment in which no IMERG data are assimilated. Several diagnostics provide insight into the nature of IMERG’s contribution to CaPA. For the most successful configuration, with a QI threshold of 0.3, IMERG’s impact is mostly found in the warmer parts of the domain, i.e., in northern US states and in British Columbia. Spatial means of the temporal sums of absolute differences between CaPA’s analyses with and without IMERG indicate that this product also contributes meaningfully over land areas covered by snow, and areas where air temperature is below −2 °C (where precipitation is assumed to be in solid phase).
Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
►▼
Show Figures
![](https://pub.mdpi-res.com/atmosphere/atmosphere-15-00763/article_deploy/html/images/atmosphere-15-00763-g001-550.jpg?1719481726)
Figure 1
Open AccessArticle
Do Chinese Residents’ Perceptions of Air Pollution Affect Their Evaluation of Central Government Performance? The Moderating Role of Environmental Knowledge
by
Yifei Shen, Chuntian Lu and Meng Liu
Atmosphere 2024, 15(7), 762; https://doi.org/10.3390/atmos15070762 - 26 Jun 2024
Abstract
In China, winning the battle for blue skies is a focal point of the central government’s environmental governance efforts. Public evaluations provide validity and legitimacy to the Chinese government’s top-level design for environmental governance. This study utilizes data from two waves of the
[...] Read more.
In China, winning the battle for blue skies is a focal point of the central government’s environmental governance efforts. Public evaluations provide validity and legitimacy to the Chinese government’s top-level design for environmental governance. This study utilizes data from two waves of the Chinese General Social Survey (CGSS) conducted in 2013 and 2021, paired with objective air quality data, to conduct a longitudinal analysis of public evaluation of central government environmental governance in China. Furthermore, it explores the relationships between perceived air pollution, objective air quality, environmental knowledge, and public assessment of central government environmental performance. The findings indicate the following: (1) Over the past decade, there has been a noticeable improvement in air quality in China, leading to a significant enhancement in public perception of the central government’s environmental performance. (2) Subjective perceptions of air pollution have a significant negative impact on evaluations of the central government, whereas objective environmental governance measures do not exhibit significant effects. (3) Environmental knowledge plays a negative moderating role in the relationship between perceived air pollution and public assessment of central government environmental performance; individuals with higher levels of environmental knowledge tend to express greater dissatisfaction with the central government’s environmental performance upon perceiving air pollution. These research findings offer valuable insights for informing the formulation of environmental governance policies by the central government of China and provide lessons for other developing and highly polluting countries.
Full article
(This article belongs to the Special Issue Toxicology and Health Effects of Air Pollution)
Open AccessArticle
Deep Learning for Flash Drought Detection: A Case Study in Northeastern Brazil
by
Humberto A. Barbosa, Catarina O. Buriti and T. V. Lakshmi Kumar
Atmosphere 2024, 15(7), 761; https://doi.org/10.3390/atmos15070761 - 26 Jun 2024
Abstract
Flash droughts (FDs) pose significant challenges for accurate detection due to their short duration. Conventional drought monitoring methods have difficultly capturing this rapidly intensifying phenomenon accurately. Machine learning models are increasingly useful for detecting droughts after training the models with data. Northeastern Brazil
[...] Read more.
Flash droughts (FDs) pose significant challenges for accurate detection due to their short duration. Conventional drought monitoring methods have difficultly capturing this rapidly intensifying phenomenon accurately. Machine learning models are increasingly useful for detecting droughts after training the models with data. Northeastern Brazil (NEB) has been a hot spot for FD events with significant ecological damage in recent years. This research introduces a novel 2D convolutional neural network (CNN) designed to identify spatial FDs in historical simulations based on multiple environmental factors and thresholds as inputs. Our model, trained with hydro-climatic data, provides a probabilistic drought detection map across northeastern Brazil (NEB) in 2012 as its output. Additionally, we examine future changes in FDs using the Coupled Model Intercomparison Project Phase 6 (CMIP6) driven by outputs from Shared Socioeconomic Pathways (SSPs) under the SSP5-8.5 scenario of 2024–2050. Our results demonstrate that the proposed spatial FD-detecting model based on 2D CNN architecture and the methodology for robust learning show promise for regional comprehensive FD monitoring. Finally, considerable spatial variability of FDs across NEB was observed during 2012 and 2024–2050, which was particularly evident in the São Francisco River Basin. This research significantly contributes to advancing our understanding of flash droughts, offering critical insights for informed water resource management and bolstering resilience against the impacts of flash droughts.
Full article
(This article belongs to the Special Issue Drought Monitoring, Prediction and Impacts)
Open AccessArticle
Research on Validation Method on Retrieval of Atmospheric Temperature and Humidity Profile Using a Microwave Sounder
by
Qiurui He, Jiaoyang Li, Ruiling Zhang, Junqi Jia and Xiao Guo
Atmosphere 2024, 15(7), 760; https://doi.org/10.3390/atmos15070760 - 26 Jun 2024
Abstract
The commonly used reference atmospheric profiles for the validation of retrieved atmospheric profiles for microwave sounders have bias compared with real atmospheric profile values, which is detrimental to the validation of the retrieval. Microwave sounder observations are the direct measurements of microwave radiation
[...] Read more.
The commonly used reference atmospheric profiles for the validation of retrieved atmospheric profiles for microwave sounders have bias compared with real atmospheric profile values, which is detrimental to the validation of the retrieval. Microwave sounder observations are the direct measurements of microwave radiation in atmospheric conditions and are a true representation of the status of the atmosphere. This paper proposed a validation method for the retrieved atmospheric temperature and atmospheric humidity profiles of the satellite-based microwave sounder using its own in-orbit observations. The validation experiments are performed both for the retrievals of the microwave temperature sounder-II (Xi’an Branch, China Academy of Space Technology, Xi’an, China. MWTS-II) and the microwave humidity and temperature sounder (National Space Science Center, Chinese Academy of Sciences, Beijing, China. MWHTS). The validation results show that the retrieved temperature profiles of MWTS-II have higher accuracy compared to the temperature profiles of ERA5 in the atmospheric pressure range of 3–30 hPa, and the accuracy of the rest of the pressure range is comparable between the profiles of ERA5 and the retrieved profiles. And the retrieved temperature profiles of MWHTS have higher accuracy compared to the temperature profiles of ERA5 in the atmospheric pressure level around 50 hPa and lower accuracy in the rest of the pressure levels. In addition, the retrieved humidity profiles of MWHTS have higher accuracy compared to the humidity profiles of ERA5 in the atmospheric pressure range of 350–925 hPa. The proposed validation method for the retrieved atmospheric temperature and atmospheric humidity profiles of MWHTS using its own observations is promising for improving the feasibility and reliability of the validation, and can be a good reference for the application of the satellite in-orbit observations and the optimization of the microwave sounders.
Full article
(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)
►▼
Show Figures
![](https://pub.mdpi-res.com/atmosphere/atmosphere-15-00760/article_deploy/html/images/atmosphere-15-00760-g001-550.jpg?1719396126)
Figure 1
Open AccessArticle
Endotoxins in Household Dust in Northern China: Associations with Home Environment Factors and Childhood Asthma and Allergies
by
Yuxuan Zhao, Yixin Liu, Lianwang Cui, Jing Hou, Feng Gao, Dan Norback and Yuexia Sun
Atmosphere 2024, 15(7), 759; https://doi.org/10.3390/atmos15070759 - 26 Jun 2024
Abstract
The available information on endotoxin in Chinese households is limited and there is inconsistency regarding its impact on asthma and allergies in children. A case-control study was performed in 324 homes in Tianjin, China. Linear regression analysis was performed to identify the determinants
[...] Read more.
The available information on endotoxin in Chinese households is limited and there is inconsistency regarding its impact on asthma and allergies in children. A case-control study was performed in 324 homes in Tianjin, China. Linear regression analysis was performed to identify the determinants of endotoxin concentrations in household dust. Logistic regression models were employed to investigate the associations of endotoxin concentrations with asthma and allergies in children. Endotoxin concentrations were determined from 284 valid dust samples, ranging from 94 to 11,625 EU/g, with a mean concentration of 3638 EU/g. We found a significant positive association between endotoxin concentrations and children’s current asthma. Old houses, ventilation systems without exhaust fans and windows opened infrequently were related to higher concentrations of endotoxins. In conclusion, endotoxin exposure in the home might be a risk factor for current asthma in children. Strategies for controlling endotoxin concentrations such as building maintenance and ventilation improvements are recommended.
Full article
(This article belongs to the Special Issue Toxicology and Health Effects of Air Pollution)
►▼
Show Figures
![](https://pub.mdpi-res.com/atmosphere/atmosphere-15-00759/article_deploy/html/images/atmosphere-15-00759-g001-550.jpg?1719395619)
Figure 1
![Atmosphere atmosphere-logo](https://pub.mdpi-res.com/img/journals/atmosphere-logo.png?88fe2866c16662af)
Journal Menu
► ▼ Journal Menu-
- Atmosphere Home
- Aims & Scope
- Editorial Board
- Reviewer Board
- Topical Advisory Panel
- Instructions for Authors
- Special Issues
- Topics
- Sections & Collections
- Article Processing Charge
- Indexing & Archiving
- Editor’s Choice Articles
- Most Cited & Viewed
- Journal Statistics
- Journal History
- Journal Awards
- Society Collaborations
- Editorial Office
Journal Browser
► ▼ Journal BrowserHighly Accessed Articles
Latest Books
E-Mail Alert
News
Topics
Topic in
Atmosphere, Energies, JMSE, Sustainability, Wind
Wind, Wave and Tidal Energy Technologies in China
Topic Editors: Wei Shi, Qihu Sheng, Fengmei Jing, Dahai Zhang, Puyang ZhangDeadline: 31 July 2024
Topic in
Atmosphere, Buildings, Materials, Remote Sensing, Sensors
Condition Perception and Performance Evaluation of Engineering Structures
Topic Editors: Jingzhou Xin, Hong Zhang, Yan Jiang, Simon X. YangDeadline: 31 August 2024
Topic in
Atmosphere, Climate, Environments, Remote Sensing, Sustainability
Atmospheric Chemistry, Aging, and Dynamics
Topic Editors: Zechen Yu, Myoseon Jang, Zhonghua ZhengDeadline: 30 September 2024
Topic in
Applied Sciences, Atmosphere, IJGI, Remote Sensing, Sustainability
Technological Innovation and Emerging Operational Applications in Digital Earth
Topic Editors: Zhihua Zhang, M. James C. CrabbeDeadline: 17 October 2024
![loading...](https://pub.mdpi-res.com/img/loading_circle.gif?9a82694213036313?1719563568)
Conferences
Special Issues
Special Issue in
Atmosphere
Numerical Weather Prediction Models and Ensemble Prediction Systems
Guest Editor: Petroula LoukaDeadline: 1 July 2024
Special Issue in
Atmosphere
Understanding and Simulating Air–Sea Interactions under Extreme Weather and Climate Conditions (2nd Edition)
Guest Editor: Xiangbo FengDeadline: 10 July 2024
Special Issue in
Atmosphere
Air Quality in Metropolitan Areas and Megacities
Guest Editors: Thiago Nogueira, Taciana Toledo De Almeida Albuquerque, Rodrigo J. Seguel, Manousos Ioannis Manousakas, Néstor Y. RojasDeadline: 26 July 2024
Special Issue in
Atmosphere
Observations and Analysis of Upper Atmosphere
Guest Editors: Shican Qiu, Guozhu LiDeadline: 9 August 2024
Topical Collections
Topical Collection in
Atmosphere
Measurement of Exposure to Air Pollution
Collection Editor: Luca Stabile
Topical Collection in
Atmosphere
Livestock Odor Issues and Air Quality
Collection Editor: Jacek Koziel
Topical Collection in
Atmosphere
Indoor Air Quality: From Sampling to Risk Assessment in the Light of New Legislations
Collection Editors: Pasquale Avino, Gaetano Settimo